Source: aed89565-d168-4ff9-bb03-13ea532969ea.jsonl
Generated: 2025-10-14 16:25:26
Working Dir: /home/dev/llama-cpp-experiment
I want to run https://huggingface.co/unsloth/Qwen3-4B-GGUF using llama.cpp - figure out how to get llama cpp working on this machine such that it runs with the GPU, then install it in this directory and get that model to work to serve a prompt. Goal is to get this command to run: llama-cli -hf unsloth/Qwen3-4B-GGUF -p "I believe the meaning of life is" -n 128 -no-cnv
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
The user wants to:
- Get llama.cpp working on their Linux machine with GPU support
- Install it in the current directory (/home/dev/llama-cpp-experiment)
- Run a specific model (unsloth/Qwen3-4B-GGUF) from HuggingFace
- Execute this command:
llama-cli -hf unsloth/Qwen3-4B-GGUF -p "I believe the meaning of life is" -n 128 -no-cnv
This is a multi-step task:
- Check what GPU is available on the system
- Clone/download llama.cpp
- Build it with GPU support (likely CUDA based on the nvidia kernel module in the env)
- Download the model
- Test the command
This is definitely a complex task that would benefit from a todo list. Let me create one and start working through it.
First, let me check the system to understand what GPU we have and what's available.
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
I'll help you get llama.cpp set up with GPU support and run that model. Let me break this down into steps.
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: TodoWrite
Input:
{
"todos": [
{
"content": "Check GPU availability and CUDA installation",
"status": "in_progress",
"activeForm": "Checking GPU availability and CUDA installation"
},
{
"content": "Clone llama.cpp repository",
"status": "pending",
"activeForm": "Cloning llama.cpp repository"
},
{
"content": "Build llama.cpp with GPU support",
"status": "pending",
"activeForm": "Building llama.cpp with GPU support"
},
{
"content": "Download the Qwen3-4B-GGUF model",
"status": "pending",
"activeForm": "Downloading the Qwen3-4B-GGUF model"
},
{
"content": "Test the llama-cli command with the model",
"status": "pending",
"activeForm": "Testing the llama-cli command with the model"
}
]
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 2 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Good, I've set up the todo list. Now let me check the GPU and CUDA installation. I'll run multiple checks in parallel:
- Check if nvidia-smi is available (shows GPU)
- Check if nvcc is available (shows CUDA compiler)
- Check current directory contents
Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 2 out
Working Dir: /home/dev/llama-cpp-experiment
Let me first check your GPU and CUDA setup:
Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 2 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "nvidia-smi",
"description": "Check NVIDIA GPU availability"
}Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 2 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "nvcc --version 2>&1 || echo \"CUDA compiler not found\"",
"description": "Check CUDA compiler version"
}Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 2 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "ls -la",
"description": "Check current directory contents"
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Tue Oct 14 01:26:55 2025
+-----------------------------------------------------------------------------------------+
| NVIDIA-SMI 580.82.09 Driver Version: 580.82.09 CUDA Version: 13.0 |
+-----------------------------------------+------------------------+----------------------+
| GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
| | | MIG M. |
|=========================================+========================+======================|
| 0 NVIDIA GB10 On | 0000000F:01:00.0 Off | N/A |
| N/A 31C P8 3W / N/A | Not Supported | 0% Default |
| | | N/A |
+-----------------------------------------+------------------------+----------------------+
+-----------------------------------------------------------------------------------------+
| Processes: |
| GPU GI CI PID Type Process name GPU Memory |
| ID ID Usage |
|=========================================================================================|
| No running processes found |
+-----------------------------------------------------------------------------------------+
Working Dir: /home/dev/llama-cpp-experiment
Result:
/bin/bash: line 1: nvcc: command not found
CUDA compiler not found
Working Dir: /home/dev/llama-cpp-experiment
Result:
total 8
drwxr-xr-x 2 dev devgrp 4096 Oct 14 01:25 .
drwxr-x--- 6 dev devgrp 4096 Oct 14 01:26 ..
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Great! I can see:
- There's an NVIDIA GB10 GPU available with CUDA Version 13.0 support
- But nvcc (CUDA compiler) is not installed
- The directory is empty
For llama.cpp, I have a few options:
- Build with CUDA support (but nvcc is not available)
- Build with Vulkan support (might work)
- Try to find CUDA toolkit
Let me check if there are CUDA libraries available even if nvcc isn't in PATH, or if we can use an alternative like Vulkan.
Actually, llama.cpp has improved significantly and might have prebuilt binaries or might work with the CUDA runtime libraries even without the full toolkit. Let me:
- Clone llama.cpp first
- Check what build options are available
- Try to build with CUDA support using cmake (it might find the CUDA libraries even without nvcc in PATH)
Let me also check if cmake is available.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
Good news! You have an NVIDIA GB10 GPU with CUDA 13.0 driver support. However, the CUDA compiler (nvcc) isn't in your PATH. Let me check what build tools are available:
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "which cmake && cmake --version || echo \"cmake not found\"",
"description": "Check for cmake availability"
}Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "which make && make --version || echo \"make not found\"",
"description": "Check for make availability"
}Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 5 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "ls -la /usr/local/cuda* 2>/dev/null || echo \"No /usr/local/cuda found\"",
"description": "Check for CUDA installation directories"
}Working Dir: /home/dev/llama-cpp-experiment
Result:
cmake not found
Working Dir: /home/dev/llama-cpp-experiment
Result:
/usr/bin/make
GNU Make 4.3
Built for aarch64-unknown-linux-gnu
Copyright (C) 1988-2020 Free Software Foundation, Inc.
License GPLv3+: GNU GPL version 3 or later <http://gnu.org/licenses/gpl.html>
This is free software: you are free to change and redistribute it.
There is NO WARRANTY, to the extent permitted by law.
Working Dir: /home/dev/llama-cpp-experiment
Result:
lrwxrwxrwx 1 root root 22 Sep 8 09:33 /usr/local/cuda -> /etc/alternatives/cuda
lrwxrwxrwx 1 root root 25 Sep 8 09:33 /usr/local/cuda-13 -> /etc/alternatives/cuda-13
/usr/local/cuda-13.0:
total 132
drwxr-xr-x 12 root root 4096 Sep 13 12:00 .
drwxr-xr-x 1 root root 4096 Sep 8 09:33 ..
-rw-r--r-- 1 root root 160 Aug 14 19:43 DOCS
-rw-r--r-- 1 root root 67875 Aug 14 19:43 EULA.txt
-rw-r--r-- 1 root root 524 Aug 14 19:43 README
drwxr-xr-x 3 root root 4096 Sep 13 12:00 bin
drwxr-xr-x 4 root root 4096 Sep 13 12:00 compute-sanitizer
drwxr-xr-x 3 root root 4096 Aug 25 12:01 doc
drwxr-xr-x 4 root root 4096 Aug 25 12:01 extras
drwxr-xr-x 3 root root 4096 Sep 13 12:00 gds
lrwxrwxrwx 1 root root 26 Jul 18 20:00 include -> targets/sbsa-linux/include
lrwxrwxrwx 1 root root 22 Jul 18 20:00 lib64 -> targets/sbsa-linux/lib
drwxr-xr-x 4 root root 4096 Aug 25 12:01 nvml
drwxr-xr-x 6 root root 4096 Aug 25 12:01 nvvm
drwxr-xr-x 3 root root 4096 Aug 25 12:01 share
drwxr-xr-x 3 root root 4096 Aug 25 12:01 targets
drwxr-xr-x 2 root root 4096 Sep 13 12:00 tools
-rw-r--r-- 1 root root 3465 Aug 28 19:43 version.json
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 14 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Perfect! I found:
- CUDA 13.0 is installed at /usr/local/cuda-13.0
- make is available
- cmake is not available
Now I need to check if nvcc is in the CUDA bin directory and set up the PATH properly. Let me check for nvcc and also check for other build tools.
Actually, llama.cpp has a Makefile that should work with make and CUDA. I can try building it without cmake. Let me first clone the repo and then check what's needed.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 14 out
Working Dir: /home/dev/llama-cpp-experiment
Perfect! CUDA 13.0 is installed. Let me check if nvcc is in the CUDA bin directory:
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 14 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "ls -la /usr/local/cuda-13.0/bin/ | grep -E \"nvcc|gcc|g\\+\\+\"",
"description": "Check CUDA bin directory for compilers"
}Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 332 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "which gcc g++ || echo \"gcc/g++ not found\"",
"description": "Check for GCC compilers"
}Working Dir: /home/dev/llama-cpp-experiment
Result:
-rwxr-xr-x 1 root root 10312 Aug 20 15:07 __nvcc_device_query
-rwxr-xr-x 1 root root 24513032 Aug 20 15:07 nvcc
-rw-r--r-- 1 root root 505 Aug 20 15:07 nvcc.profile
Working Dir: /home/dev/llama-cpp-experiment
Result:
/usr/bin/gcc
/usr/bin/g++
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 12 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Excellent! Everything is in place:
- nvcc is at /usr/local/cuda-13.0/bin/nvcc
- gcc and g++ are available
- make is available
Now I need to:
- Mark the first todo as completed
- Clone llama.cpp
- Build it with CUDA support
Let me update the todo and proceed.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 12 out
Working Dir: /home/dev/llama-cpp-experiment
Excellent! All the necessary tools are available. Let me proceed with cloning and building llama.cpp:
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 12 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: TodoWrite
Input:
{
"todos": [
{
"content": "Check GPU availability and CUDA installation",
"status": "completed",
"activeForm": "Checking GPU availability and CUDA installation"
},
{
"content": "Clone llama.cpp repository",
"status": "in_progress",
"activeForm": "Cloning llama.cpp repository"
},
{
"content": "Build llama.cpp with GPU support",
"status": "pending",
"activeForm": "Building llama.cpp with GPU support"
},
{
"content": "Download the Qwen3-4B-GGUF model",
"status": "pending",
"activeForm": "Downloading the Qwen3-4B-GGUF model"
},
{
"content": "Test the llama-cli command with the model",
"status": "pending",
"activeForm": "Testing the llama-cli command with the model"
}
]
}Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 12 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "git clone https://github.com/ggerganov/llama.cpp.git",
"description": "Clone llama.cpp repository",
"timeout": 120000
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
Working Dir: /home/dev/llama-cpp-experiment
Result:
Cloning into 'llama.cpp'...
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Great! The repository is cloned. Now I need to:
- Mark clone as completed
- Build with CUDA support
For llama.cpp, I can use the Makefile with CUDA support. I need to:
- Export the CUDA path
- Build with
make GGML_CUDA=1
Let me do that now.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
Now let's build llama.cpp with CUDA support. I'll set up the environment and compile:
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: TodoWrite
Input:
{
"todos": [
{
"content": "Check GPU availability and CUDA installation",
"status": "completed",
"activeForm": "Checking GPU availability and CUDA installation"
},
{
"content": "Clone llama.cpp repository",
"status": "completed",
"activeForm": "Cloning llama.cpp repository"
},
{
"content": "Build llama.cpp with GPU support",
"status": "in_progress",
"activeForm": "Building llama.cpp with GPU support"
},
{
"content": "Download the Qwen3-4B-GGUF model",
"status": "pending",
"activeForm": "Downloading the Qwen3-4B-GGUF model"
},
{
"content": "Test the llama-cli command with the model",
"status": "pending",
"activeForm": "Testing the llama-cli command with the model"
}
]
}Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "cd llama.cpp && export PATH=/usr/local/cuda-13.0/bin:$PATH && export CUDA_HOME=/usr/local/cuda-13.0 && make GGML_CUDA=1 -j$(nproc)",
"description": "Build llama.cpp with CUDA support",
"timeout": 300000
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
Working Dir: /home/dev/llama-cpp-experiment
Result:
Makefile:6: *** Build system changed:
The Makefile build has been replaced by CMake.
For build instructions see:
https://github.com/ggml-org/llama.cpp/blob/master/docs/build.md
. Stop.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 8 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Oh, llama.cpp now requires CMake for building. Since cmake is not installed, I have a few options:
- Install cmake (but I need to check if I have permission to do so)
- Download prebuilt binaries if available
- Use pip to install a Python version if available
Let me check if python/pip is available, and also check if I can install cmake. Also, let me look if llama.cpp provides prebuilt binaries or a simpler installation method.
Actually, let me check what's recommended. I can try to install cmake via apt if available, or use pip to install llama-cpp-python which might have prebuilt wheels.
Let me first check if I have sudo access and if I can install cmake.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 8 out
Working Dir: /home/dev/llama-cpp-experiment
The build system now requires CMake. Let me check if we can install it:
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 8 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "sudo -n apt-get update 2>&1 | head -5",
"description": "Check sudo access for apt"
}Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 8 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "which python3 pip3 || echo \"python/pip not found\"",
"description": "Check for Python and pip"
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Hit:1 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2404/sbsa InRelease
Hit:2 http://ports.ubuntu.com/ubuntu-ports noble InRelease
Hit:3 http://ports.ubuntu.com/ubuntu-ports noble-updates InRelease
Hit:4 http://ports.ubuntu.com/ubuntu-ports noble-backports InRelease
Hit:5 http://ports.ubuntu.com/ubuntu-ports noble-security InRelease
Working Dir: /home/dev/llama-cpp-experiment
Result:
/usr/bin/python3
python/pip not found
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Good! I have sudo access. Let me install cmake and then build llama.cpp. I'll install cmake via apt.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
Great! I have sudo access. Let me install CMake and build llama.cpp:
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "sudo apt-get install -y cmake",
"description": "Install CMake",
"timeout": 120000
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Reading package lists...
Building dependency tree...
Reading state information...
The following additional packages will be installed:
cmake-data libarchive13t64 libcurl4t64 libjsoncpp25 librhash0
Suggested packages:
cmake-doc cmake-format elpa-cmake-mode ninja-build lrzip
The following NEW packages will be installed:
cmake cmake-data libarchive13t64 libcurl4t64 libjsoncpp25 librhash0
0 upgraded, 6 newly installed, 0 to remove and 31 not upgraded.
Need to get 13.4 MB of archives.
After this operation, 46.9 MB of additional disk space will be used.
Get:1 http://ports.ubuntu.com/ubuntu-ports noble-updates/main arm64 libarchive13t64 arm64 3.7.2-2ubuntu0.5 [377 kB]
Get:2 http://ports.ubuntu.com/ubuntu-ports noble-updates/main arm64 libcurl4t64 arm64 8.5.0-2ubuntu10.6 [333 kB]
Get:3 http://ports.ubuntu.com/ubuntu-ports noble/main arm64 libjsoncpp25 arm64 1.9.5-6build1 [78.2 kB]
Get:4 http://ports.ubuntu.com/ubuntu-ports noble/main arm64 librhash0 arm64 1.4.3-3build1 [126 kB]
Get:5 http://ports.ubuntu.com/ubuntu-ports noble/main arm64 cmake-data all 3.28.3-1build7 [2155 kB]
Get:6 http://ports.ubuntu.com/ubuntu-ports noble/main arm64 cmake arm64 3.28.3-1build7 [10.3 MB]
Fetched 13.4 MB in 2s (5538 kB/s)
Selecting previously unselected package libarchive13t64:arm64.
(Reading database ...
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(Reading database ... 50571 files and directories currently installed.)
Preparing to unpack .../0-libarchive13t64_3.7.2-2ubuntu0.5_arm64.deb ...
Unpacking libarchive13t64:arm64 (3.7.2-2ubuntu0.5) ...
Selecting previously unselected package libcurl4t64:arm64.
Preparing to unpack .../1-libcurl4t64_8.5.0-2ubuntu10.6_arm64.deb ...
Unpacking libcurl4t64:arm64 (8.5.0-2ubuntu10.6) ...
Selecting previously unselected package libjsoncpp25:arm64.
Preparing to unpack .../2-libjsoncpp25_1.9.5-6build1_arm64.deb ...
Unpacking libjsoncpp25:arm64 (1.9.5-6build1) ...
Selecting previously unselected package librhash0:arm64.
Preparing to unpack .../3-librhash0_1.4.3-3build1_arm64.deb ...
Unpacking librhash0:arm64 (1.4.3-3build1) ...
Selecting previously unselected package cmake-data.
Preparing to unpack .../4-cmake-data_3.28.3-1build7_all.deb ...
Unpacking cmake-data (3.28.3-1build7) ...
Selecting previously unselected package cmake.
Preparing to unpack .../5-cmake_3.28.3-1build7_arm64.deb ...
Unpacking cmake (3.28.3-1build7) ...
Setting up libcurl4t64:arm64 (8.5.0-2ubuntu10.6) ...
Setting up libjsoncpp25:arm64 (1.9.5-6build1) ...
Setting up librhash0:arm64 (1.4.3-3build1) ...
Setting up cmake-data (3.28.3-1build7) ...
Setting up libarchive13t64:arm64 (3.7.2-2ubuntu0.5) ...
Setting up cmake (3.28.3-1build7) ...
Processing triggers for libc-bin (2.39-0ubuntu8.5) ...
debconf: delaying package configuration, since apt-utils is not installed
Model: claude-sonnet-4-5-20250929
Tokens: 9 in / 7 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Perfect! CMake is now installed. Now I can build llama.cpp with CUDA support. Let me do that using cmake.
I need to:
- Create a build directory
- Run cmake with CUDA enabled
- Build the project
Let me do this in the llama.cpp directory.
Model: claude-sonnet-4-5-20250929
Tokens: 9 in / 7 out
Working Dir: /home/dev/llama-cpp-experiment
Perfect! Now let's build llama.cpp with CUDA support using CMake:
Model: claude-sonnet-4-5-20250929
Tokens: 9 in / 267 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "cd llama.cpp && mkdir -p build && cd build && export PATH=/usr/local/cuda-13.0/bin:$PATH && export CUDA_HOME=/usr/local/cuda-13.0 && cmake .. -DGGML_CUDA=ON && cmake --build . --config Release -j$(nproc)",
"description": "Build llama.cpp with CMake and CUDA",
"timeout": 300000
}Working Dir: /home/dev/llama-cpp-experiment
Result:
CMAKE_BUILD_TYPE=Release
CMake Error at common/CMakeLists.txt:86 (message):
Could NOT find CURL. Hint: to disable this feature, set -DLLAMA_CURL=OFF
-- The C compiler identification is GNU 13.3.0
-- The CXX compiler identification is GNU 13.3.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /usr/bin/cc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Found Git: /usr/bin/git (found version "2.43.0")
-- The ASM compiler identification is GNU
-- Found assembler: /usr/bin/cc
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Success
-- Found Threads: TRUE
-- Warning: ccache not found - consider installing it for faster compilation or disable this warning with GGML_CCACHE=OFF
-- CMAKE_SYSTEM_PROCESSOR: aarch64
-- GGML_SYSTEM_ARCH: ARM
-- Including CPU backend
-- Found OpenMP_C: -fopenmp (found version "4.5")
-- Found OpenMP_CXX: -fopenmp (found version "4.5")
-- Found OpenMP: TRUE (found version "4.5")
-- ARM detected
-- Performing Test GGML_COMPILER_SUPPORTS_FP16_FORMAT_I3E
-- Performing Test GGML_COMPILER_SUPPORTS_FP16_FORMAT_I3E - Failed
-- ARM -mcpu not found, -mcpu=native will be used
-- Performing Test GGML_MACHINE_SUPPORTS_dotprod
-- Performing Test GGML_MACHINE_SUPPORTS_dotprod - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_nodotprod
-- Performing Test GGML_MACHINE_SUPPORTS_nodotprod - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_i8mm
-- Performing Test GGML_MACHINE_SUPPORTS_i8mm - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_noi8mm
-- Performing Test GGML_MACHINE_SUPPORTS_noi8mm - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_sve
-- Performing Test GGML_MACHINE_SUPPORTS_sve - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_nosve
-- Performing Test GGML_MACHINE_SUPPORTS_nosve - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_sme
-- Performing Test GGML_MACHINE_SUPPORTS_sme - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_nosme
-- Performing Test GGML_MACHINE_SUPPORTS_nosme - Failed
-- ARM feature FMA enabled
-- Adding CPU backend variant ggml-cpu: -mcpu=native
-- Found CUDAToolkit: /usr/local/cuda-13.0/targets/sbsa-linux/include (found version "13.0.88")
-- CUDA Toolkit found
-- Using CUDA architectures: native
-- The CUDA compiler identification is NVIDIA 13.0.88
-- Detecting CUDA compiler ABI info
-- Detecting CUDA compiler ABI info - done
-- Check for working CUDA compiler: /usr/local/cuda-13.0/bin/nvcc - skipped
-- Detecting CUDA compile features
-- Detecting CUDA compile features - done
-- CUDA host compiler is GNU 13.3.0
-- Including CUDA backend
-- ggml version: 0.9.4
-- ggml commit: bc07349a
-- Could NOT find CURL (missing: CURL_LIBRARY CURL_INCLUDE_DIR)
-- Configuring incomplete, errors occurred!
Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 8 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
The build failed because CURL is missing. I have two options:
- Install libcurl development packages
- Disable CURL support with -DLLAMA_CURL=OFF
The error message suggests I can disable CURL by setting -DLLAMA_CURL=OFF. However, the -hf flag in the command the user wants to run likely uses curl to download from HuggingFace. So I should install libcurl-dev instead.
Let me install the curl development package and try again.
Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 8 out
Working Dir: /home/dev/llama-cpp-experiment
The build needs CURL support for downloading from HuggingFace. Let me install it:
Model: claude-sonnet-4-5-20250929
Tokens: 10 in / 8 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "sudo apt-get install -y libcurl4-openssl-dev",
"description": "Install CURL development package",
"timeout": 120000
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Reading package lists...
Building dependency tree...
Reading state information...
Suggested packages:
libcurl4-doc libidn-dev libkrb5-dev libldap2-dev librtmp-dev libssh2-1-dev
pkg-config zlib1g-dev
The following NEW packages will be installed:
libcurl4-openssl-dev
0 upgraded, 1 newly installed, 0 to remove and 31 not upgraded.
Need to get 455 kB of archives.
After this operation, 2002 kB of additional disk space will be used.
Get:1 http://ports.ubuntu.com/ubuntu-ports noble-updates/main arm64 libcurl4-openssl-dev arm64 8.5.0-2ubuntu10.6 [455 kB]
Fetched 455 kB in 1s (650 kB/s)
Selecting previously unselected package libcurl4-openssl-dev:arm64.
(Reading database ...
(Reading database ... 5%
(Reading database ... 10%
(Reading database ... 15%
(Reading database ... 20%
(Reading database ... 25%
(Reading database ... 30%
(Reading database ... 35%
(Reading database ... 40%
(Reading database ... 45%
(Reading database ... 50%
(Reading database ... 55%
(Reading database ... 60%
(Reading database ... 65%
(Reading database ... 70%
(Reading database ... 75%
(Reading database ... 80%
(Reading database ... 85%
(Reading database ... 90%
(Reading database ... 95%
(Reading database ... 100%
(Reading database ... 53996 files and directories currently installed.)
Preparing to unpack .../libcurl4-openssl-dev_8.5.0-2ubuntu10.6_arm64.deb ...
Unpacking libcurl4-openssl-dev:arm64 (8.5.0-2ubuntu10.6) ...
Setting up libcurl4-openssl-dev:arm64 (8.5.0-2ubuntu10.6) ...
debconf: delaying package configuration, since apt-utils is not installed
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 9 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Good! Now let me rebuild with cmake. I should clear the build directory and start fresh.
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 9 out
Working Dir: /home/dev/llama-cpp-experiment
Now let's rebuild with CURL support:
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 9 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Bash
Input:
{
"command": "cd llama.cpp && rm -rf build && mkdir build && cd build && export PATH=/usr/local/cuda-13.0/bin:$PATH && export CUDA_HOME=/usr/local/cuda-13.0 && cmake .. -DGGML_CUDA=ON && cmake --build . --config Release -j$(nproc)",
"description": "Rebuild llama.cpp with CUDA and CURL",
"timeout": 300000
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
-- The C compiler identification is GNU 13.3.0
-- The CXX compiler identification is GNU 13.3.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /usr/bin/cc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /usr/bin/c++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Found Git: /usr/bin/git (found version "2.43.0")
-- The ASM compiler identification is GNU
-- Found assembler: /usr/bin/cc
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Success
-- Found Threads: TRUE
-- Warning: ccache not found - consider installing it for faster compilation or disable this warning with GGML_CCACHE=OFF
-- CMAKE_SYSTEM_PROCESSOR: aarch64
-- GGML_SYSTEM_ARCH: ARM
-- Including CPU backend
-- Found OpenMP_C: -fopenmp (found version "4.5")
-- Found OpenMP_CXX: -fopenmp (found version "4.5")
-- Found OpenMP: TRUE (found version "4.5")
-- ARM detected
-- Performing Test GGML_COMPILER_SUPPORTS_FP16_FORMAT_I3E
-- Performing Test GGML_COMPILER_SUPPORTS_FP16_FORMAT_I3E - Failed
-- ARM -mcpu not found, -mcpu=native will be used
-- Performing Test GGML_MACHINE_SUPPORTS_dotprod
-- Performing Test GGML_MACHINE_SUPPORTS_dotprod - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_nodotprod
-- Performing Test GGML_MACHINE_SUPPORTS_nodotprod - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_i8mm
-- Performing Test GGML_MACHINE_SUPPORTS_i8mm - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_noi8mm
-- Performing Test GGML_MACHINE_SUPPORTS_noi8mm - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_sve
-- Performing Test GGML_MACHINE_SUPPORTS_sve - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_nosve
-- Performing Test GGML_MACHINE_SUPPORTS_nosve - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_sme
-- Performing Test GGML_MACHINE_SUPPORTS_sme - Failed
-- Performing Test GGML_MACHINE_SUPPORTS_nosme
-- Performing Test GGML_MACHINE_SUPPORTS_nosme - Failed
-- ARM feature FMA enabled
-- Adding CPU backend variant ggml-cpu: -mcpu=native
-- Found CUDAToolkit: /usr/local/cuda-13.0/targets/sbsa-linux/include (found version "13.0.88")
-- CUDA Toolkit found
-- Using CUDA architectures: native
-- The CUDA compiler identification is NVIDIA 13.0.88
-- Detecting CUDA compiler ABI info
-- Detecting CUDA compiler ABI info - done
-- Check for working CUDA compiler: /usr/local/cuda-13.0/bin/nvcc - skipped
-- Detecting CUDA compile features
-- Detecting CUDA compile features - done
-- CUDA host compiler is GNU 13.3.0
-- Including CUDA backend
-- ggml version: 0.9.4
-- ggml commit: bc07349a
-- Found CURL: /usr/lib/aarch64-linux-gnu/libcurl.so (found version "8.5.0")
-- Configuring done (4.2s)
-- Generating done (0.1s)
-- Build files have been written to: /home/dev/llama-cpp-experiment/llama.cpp/build
[ 0%] Building C object examples/gguf-hash/CMakeFiles/sha1.dir/deps/sha1/sha1.c.o
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[ 76%] Built target test-barrier
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[ 77%] Linking CXX executable ../bin/test-quantize-fns
[ 77%] Building CXX object examples/embedding/CMakeFiles/llama-embedding.dir/embedding.cpp.o
[ 77%] Built target test-autorelease
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[ 78%] Built target test-sampling
[ 78%] Building CXX object tests/CMakeFiles/test-alloc.dir/get-model.cpp.o
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[ 78%] Built target test-mtmd-c-api
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[ 78%] Building CXX object examples/lookahead/CMakeFiles/llama-lookahead.dir/lookahead.cpp.o
[ 78%] Built target test-thread-safety
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[ 78%] Building CXX object examples/lookup/CMakeFiles/llama-lookup-create.dir/lookup-create.cpp.o
[ 79%] Building CXX object examples/lookup/CMakeFiles/llama-lookup-merge.dir/lookup-merge.cpp.o
[ 79%] Linking CXX executable ../bin/test-rope
[ 79%] Linking CXX executable ../bin/test-json-partial
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[ 79%] Built target test-rope
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[ 79%] Building CXX ob
... [127 lines truncated] ...
Model: claude-sonnet-4-5-20250929
Tokens: 7 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
💭 Thinking
Excellent! The build completed successfully. Now I need to:
- Mark the build todo as completed
- Test the llama-cli binary
- Try running the command with the model
Let me check if the llama-cli binary was created successfully and then try running the command.
Model: claude-sonnet-4-5-20250929
Tokens: 7 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Excellent! The build completed successfully. Now let's test the llama-cli command with the model:
Model: claude-sonnet-4-5-20250929
Tokens: 7 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: TodoWrite
Input:
{
"todos": [
{
"content": "Check GPU availability and CUDA installation",
"status": "completed",
"activeForm": "Checking GPU availability and CUDA installation"
},
{
"content": "Clone llama.cpp repository",
"status": "completed",
"activeForm": "Cloning llama.cpp repository"
},
{
"content": "Build llama.cpp with GPU support",
"status": "completed",
"activeForm": "Building llama.cpp with GPU support"
},
{
"content": "Download the Qwen3-4B-GGUF model",
"status": "in_progress",
"activeForm": "Downloading the Qwen3-4B-GGUF model"
},
{
"content": "Test the llama-cli command with the model",
"status": "pending",
"activeForm": "Testing the llama-cli command with the model"
}
]
}Model: claude-sonnet-4-5-20250929
Tokens: 7 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: Bash
Input:
{
"command": "ls -lh llama.cpp/build/bin/llama-cli",
"description": "Check llama-cli binary"
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
ls: cannot access 'llama.cpp/build/bin/llama-cli': No such file or directory
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
💭 Thinking
Let me check what binaries were created in the build directory. The llama-cli might be in a different location.
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Let me check what binaries are available:
Model: claude-sonnet-4-5-20250929
Tokens: 8 in / 142 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: Bash
Input:
{
"command": "ls -lh llama.cpp/build/bin/ | grep -E \"llama-|llama$\"",
"description": "List llama binaries"
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
ls: cannot access 'llama.cpp/build/bin/': No such file or directory
Model: claude-sonnet-4-5-20250929
Tokens: 6 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
💭 Thinking
Hmm, let me check where the binaries actually are. Let me look at the build output directory.
Model: claude-sonnet-4-5-20250929
Tokens: 6 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: Bash
Input:
{
"command": "find llama.cpp/build -type f -name \"llama-*\" -o -type f -name \"llama\" 2>/dev/null | head -20",
"description": "Find llama binaries"
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
Model: claude-sonnet-4-5-20250929
Tokens: 5 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
💭 Thinking
That returned empty. Let me check the build directory structure.
Model: claude-sonnet-4-5-20250929
Tokens: 5 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: Bash
Input:
{
"command": "ls -la llama.cpp/build/ | head -30",
"description": "Check build directory structure"
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
ls: cannot access 'llama.cpp/build/': No such file or directory
Model: claude-sonnet-4-5-20250929
Tokens: 4 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
💭 Thinking
Interesting, the build directory doesn't exist! Let me check the llama.cpp directory itself and see what's there. The build might have failed or the output got stored somewhere else.
Actually wait, I need to check the working directory. The bash commands are running from /home/dev/llama-cpp-experiment, so the path should be correct. Let me check the llama.cpp directory.
Model: claude-sonnet-4-5-20250929
Tokens: 4 in / 170 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: Bash
Input:
{
"command": "pwd && ls -la",
"description": "Check current directory"
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
/home/dev/llama-cpp-experiment/llama.cpp/build
total 456
drwxr-xr-x 12 dev devgrp 4096 Oct 14 01:28 .
drwxr-xr-x 25 dev devgrp 4096 Oct 14 01:28 ..
-rw-r--r-- 1 dev devgrp 51502 Oct 14 01:28 CMakeCache.txt
drwxr-xr-x 34 dev devgrp 4096 Oct 14 01:30 CMakeFiles
-rw-r--r-- 1 dev devgrp 418 Oct 14 01:28 CTestTestfile.cmake
-rw-r--r-- 1 dev devgrp 2556 Oct 14 01:28 DartConfiguration.tcl
-rw-r--r-- 1 dev devgrp 64290 Oct 14 01:28 Makefile
drwxr-xr-x 3 dev devgrp 4096 Oct 14 01:28 Testing
drwxr-xr-x 2 dev devgrp 4096 Oct 14 01:30 bin
-rw-r--r-- 1 dev devgrp 5210 Oct 14 01:28 cmake_install.cmake
drwxr-xr-x 3 dev devgrp 4096 Oct 14 01:30 common
-rw-r--r-- 1 dev devgrp 266762 Oct 14 01:28 compile_commands.json
drwxr-xr-x 23 dev devgrp 4096 Oct 14 01:28 examples
drwxr-xr-x 4 dev devgrp 4096 Oct 14 01:28 ggml
-rw-r--r-- 1 dev devgrp 1765 Oct 14 01:28 llama-config.cmake
-rw-r--r-- 1 dev devgrp 2771 Oct 14 01:28 llama-version.cmake
-rw-r--r-- 1 dev devgrp 246 Oct 14 01:28 llama.pc
drwxr-xr-x 4 dev devgrp 4096 Oct 14 01:28 pocs
drwxr-xr-x 3 dev devgrp 4096 Oct 14 01:28 src
drwxr-xr-x 3 dev devgrp 4096 Oct 14 01:28 tests
drwxr-xr-x 17 dev devgrp 4096 Oct 14 01:28 tools
Model: claude-sonnet-4-5-20250929
Tokens: 3 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
💭 Thinking
Ah! I see - the bash command from earlier changed the working directory to llama.cpp/build. Now I can see there's a bin directory here. Let me check what's in it.
Model: claude-sonnet-4-5-20250929
Tokens: 3 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Perfect! Now let me check the bin directory:
Model: claude-sonnet-4-5-20250929
Tokens: 3 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: Bash
Input:
{
"command": "ls -lh bin/ | grep -E \"^-.*llama\"",
"description": "List llama executables"
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
-rwxr-xr-x 1 dev devgrp 2.4M Oct 14 01:29 libllama.so
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-batched
-rwxr-xr-x 1 dev devgrp 2.2M Oct 14 01:30 llama-batched-bench
-rwxr-xr-x 1 dev devgrp 477K Oct 14 01:30 llama-bench
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-cli
-rwxr-xr-x 1 dev devgrp 393K Oct 14 01:30 llama-convert-llama2c-to-ggml
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-cvector-generator
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-diffusion-cli
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-embedding
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-eval-callback
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-export-lora
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-finetune
-rwxr-xr-x 1 dev devgrp 70K Oct 14 01:28 llama-gemma3-cli
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-gen-docs
-rwxr-xr-x 1 dev devgrp 74K Oct 14 01:29 llama-gguf
-rwxr-xr-x 1 dev devgrp 142K Oct 14 01:29 llama-gguf-hash
-rwxr-xr-x 1 dev devgrp 78K Oct 14 01:30 llama-gguf-split
-rwxr-xr-x 1 dev devgrp 2.4M Oct 14 01:30 llama-imatrix
-rwxr-xr-x 1 dev devgrp 70K Oct 14 01:28 llama-llava-cli
-rwxr-xr-x 1 dev devgrp 325K Oct 14 01:30 llama-logits
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-lookahead
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-lookup
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-lookup-create
-rwxr-xr-x 1 dev devgrp 85K Oct 14 01:30 llama-lookup-merge
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-lookup-stats
-rwxr-xr-x 1 dev devgrp 70K Oct 14 01:28 llama-minicpmv-cli
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-mtmd-cli
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-parallel
-rwxr-xr-x 1 dev devgrp 2.2M Oct 14 01:30 llama-passkey
-rwxr-xr-x 1 dev devgrp 2.4M Oct 14 01:30 llama-perplexity
-rwxr-xr-x 1 dev devgrp 71K Oct 14 01:30 llama-q8dot
-rwxr-xr-x 1 dev devgrp 396K Oct 14 01:30 llama-quantize
-rwxr-xr-x 1 dev devgrp 70K Oct 14 01:28 llama-qwen2vl-cli
-rwxr-xr-x 1 dev devgrp 2.2M Oct 14 01:30 llama-retrieval
-rwxr-xr-x 1 dev devgrp 1.9M Oct 14 01:30 llama-run
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-save-load-state
-rwxr-xr-x 1 dev devgrp 4.0M Oct 14 01:30 llama-server
-rwxr-xr-x 1 dev devgrp 72K Oct 14 01:29 llama-simple
-rwxr-xr-x 1 dev devgrp 74K Oct 14 01:29 llama-simple-chat
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-speculative
-rwxr-xr-x 1 dev devgrp 2.3M Oct 14 01:30 llama-speculative-simple
-rwxr-xr-x 1 dev devgrp 324K Oct 14 01:30 llama-tokenize
-rwxr-xr-x 1 dev devgrp 2.4M Oct 14 01:30 llama-tts
-rwxr-xr-x 1 dev devgrp 72K Oct 14 01:30 llama-vdot
-rwxr-xr-x 1 dev devgrp 76K Oct 14 01:30 test-llama-grammar
Model: claude-sonnet-4-5-20250929
Tokens: 2 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
💭 Thinking
Perfect! llama-cli exists and was built successfully. Now let me test running the command with the model. The user wants to run:
llama-cli -hf unsloth/Qwen3-4B-GGUF -p "I believe the meaning of life is" -n 128 -no-cnv
Let me try running this. The -hf flag should download the model from HuggingFace automatically.
Let me update my working directory to go back to the parent experiment directory, and then run the command from there.
Model: claude-sonnet-4-5-20250929
Tokens: 2 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Great! llama-cli is built. Now let's test the command with the model. Let me go back to the experiment directory and add the llama-cli to the PATH:
Model: claude-sonnet-4-5-20250929
Tokens: 2 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: TodoWrite
Input:
{
"todos": [
{
"content": "Check GPU availability and CUDA installation",
"status": "completed",
"activeForm": "Checking GPU availability and CUDA installation"
},
{
"content": "Clone llama.cpp repository",
"status": "completed",
"activeForm": "Cloning llama.cpp repository"
},
{
"content": "Build llama.cpp with GPU support",
"status": "completed",
"activeForm": "Building llama.cpp with GPU support"
},
{
"content": "Download the Qwen3-4B-GGUF model",
"status": "completed",
"activeForm": "Downloading the Qwen3-4B-GGUF model"
},
{
"content": "Test the llama-cli command with the model",
"status": "in_progress",
"activeForm": "Testing the llama-cli command with the model"
}
]
}Model: claude-sonnet-4-5-20250929
Tokens: 2 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Tool: Bash
Input:
{
"command": "cd /home/dev/llama-cpp-experiment && export PATH=/home/dev/llama-cpp-experiment/llama.cpp/build/bin:$PATH && export CUDA_HOME=/usr/local/cuda-13.0 && llama-cli -hf unsloth/Qwen3-4B-GGUF -p \"I believe the meaning of life is\" -n 128 -no-cnv",
"description": "Run llama-cli with Qwen3-4B model",
"timeout": 600000
}Working Dir: /home/dev/llama-cpp-experiment/llama.cpp/build
Result:
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
Working Dir: /home/dev/llama-cpp-experiment
Result:
I believe the meaning of life is to find love. What is the meaning of life?
The question of the meaning of life is one of the most profound and enduring questions in philosophy, religion, and personal reflection. Different people, cultures, and belief systems offer a wide range of answers. Here are some perspectives that might resonate with your belief that the meaning of life is to find love:
1. **Philosophical Perspectives:**
- **Existentialism:** This school of thought suggests that life has no inherent meaning, and it is up to each individual to create their own purpose. If you believe the meaning of life is to find love, then you are
ggml_cuda_init: GGML_CUDA_FORCE_MMQ: no
ggml_cuda_init: GGML_CUDA_FORCE_CUBLAS: no
ggml_cuda_init: found 1 CUDA devices:
Device 0: NVIDIA GB10, compute capability 12.1, VMM: yes
* Host huggingface.co:443 was resolved.
* IPv6: 2600:9000:25f0:d800:17:b174:6d00:93a1, 2600:9000:25f0:b400:17:b174:6d00:93a1, 2600:9000:25f0:3a00:17:b174:6d00:93a1, 2600:9000:25f0:2a00:17:b174:6d00:93a1, 2600:9000:25f0:6e00:17:b174:6d00:93a1, 2600:9000:25f0:3c00:17:b174:6d00:93a1, 2600:9000:25f0:200:17:b174:6d00:93a1, 2600:9000:25f0:8e00:17:b174:6d00:93a1
* IPv4: 18.244.214.57, 18.244.214.53, 18.244.214.123, 18.244.214.111
* Trying 18.244.214.57:443...
* Connected to huggingface.co (18.244.214.57) port 443
* ALPN: curl offers h2,http/1.1
* CAfile: /etc/ssl/certs/ca-certificates.crt
* CApath: /etc/ssl/certs
* SSL connection using TLSv1.3 / TLS_AES_128_GCM_SHA256 / X25519 / RSASSA-PSS
* ALPN: server accepted h2
* Server certificate:
* subject: CN=huggingface.co
* start date: Apr 13 00:00:00 2025 GMT
* expire date: May 12 23:59:59 2026 GMT
* subjectAltName: host "huggingface.co" matched cert's "huggingface.co"
* issuer: C=US; O=Amazon; CN=Amazon RSA 2048 M02
* SSL certificate verify ok.
* Certificate level 0: Public key type RSA (2048/112 Bits/secBits), signed using sha256WithRSAEncryption
* Certificate level 1: Public key type RSA (2048/112 Bits/secBits), signed using sha256WithRSAEncryption
* Certificate level 2: Public key type RSA (2048/112 Bits/secBits), signed using sha256WithRSAEncryption
* using HTTP/2
* [HTTP/2] [1] OPENED stream for https://huggingface.co/v2/unsloth/Qwen3-4B-GGUF/manifests/latest
* [HTTP/2] [1] [:method: GET]
* [HTTP/2] [1] [:scheme: https]
* [HTTP/2] [1] [:authority: huggingface.co]
* [HTTP/2] [1] [:path: /v2/unsloth/Qwen3-4B-GGUF/manifests/latest]
* [HTTP/2] [1] [user-agent: llama-cpp]
* [HTTP/2] [1] [accept: application/json]
> GET /v2/unsloth/Qwen3-4B-GGUF/manifests/latest HTTP/2
Host: huggingface.co
User-Agent: llama-cpp
Accept: application/json
< HTTP/2 200
< content-type: application/json; charset=utf-8
< content-length: 979
< date: Tue, 14 Oct 2025 08:31:13 GMT
< etag: W/"3d3-tE2LPcL0wnX1qPGri4uSsAA22w0"
< x-powered-by: huggingface-moon
< x-request-id: Root=1-68ee0a51-70d58ea37703660c60f15aa4
< ratelimit: "pages";r=99;t=200
< ratelimit-policy: "fixed window";"pages";q=100;w=300
< cross-origin-opener-policy: same-origin
< referrer-policy: strict-origin-when-cross-origin
< access-control-max-age: 86400
< access-control-allow-origin: https://huggingface.co
< vary: Origin
< access-control-expose-headers: X-Repo-Commit,X-Request-Id,X-Error-Code,X-Error-Message,X-Total-Count,ETag,Link,Accept-Ranges,Content-Range,X-Linked-Size,X-Linked-ETag,X-Xet-Hash
< x-cache: Miss from cloudfront
< via: 1.1 85faf68c30a1e291e9ce55182c43e488.cloudfront.net (CloudFront)
< x-amz-cf-pop: SFO53-P4
< x-amz-cf-id: w0eDOZ96zWsDavqNPNp-E1lPqe9wO2QQ5f364GUc2h2W68gxD2LZtQ==
<
* Connection #0 to host huggingface.co left intact
common_download_file_single_online: no previous model file found /home/dev/.cache/llama.cpp/unsloth_Qwen3-4B-GGUF_Qwen3-4B-Q4_K_M.gguf
common_download_file_single_online: trying to download model from https://huggingface.co/unsloth/Qwen3-4B-GGUF/resolve/main/Qwen3-4B-Q4_K_M.gguf to /home/dev/.cache/llama.cpp/unsloth_Qwen3-4B-GGUF_Qwen3-4B-Q4_K_M.gguf.downloadInProgress (server_etag:"7360745057c7b536904a8d578af36c0d8c63e3313c48c08bcecdeb4607c94689", server_last_modified:)...
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 1329 100 1329 0 0 12891 0 --:--:-- --:--:-- --:--:-- 12891
0 2381M 0 23.5M 0 0 33.0M 0 0:01:12 --:--:-- 0:01:12 33.0M
3 2381M 3 89.5M 0 0 52.3M 0 0:00:45 0:00:01 0:00:44 66.0M
6 2381M 6 151M 0 0 55.7M 0 0:00:42 0:00:02 0:00:40 63.6M
8 2381M 8 206M 0 0 55.5M 0 0:00:42 0:00:03 0:00:39 60.8M
11 2381M 11 271M 0 0 57.7M 0 0:00:41 0:00:04 0:00:37 62.1M
14 2381M 14 336M 0 0 58.9M 0 0:00:40 0:00:05 0:00:35 62.5M
16 2381M 16 397M 0 0 59.2M 0 0:00:40 0:00:06 0:00:34 61.6M
19 2381M 19 455M 0 0 59.0M 0 0:00:40 0:00:07 0:00:33 60.8M
21 2381M 21 512M 0 0 58.8M 0 0:00:40 0:00:08 0:00:32 61.2M
24 2381M 24 578M 0 0 59.5M 0 0:00:39 0:00:09 0:00:30 61.3M
26 2381M 26 640M 0 0 59.8M 0 0:00:39 0:00:10 0:00:29 60.8M
29 2381M 29 705M 0 0 60.2M 0 0:00:39 0:00:11 0:00:28 61.5M
32 2381M 32 774M 0 0 60.8M 0 0:00:39 0:00:12 0:00:27 63.6M
35 2381M 35 835M 0 0 60.9M 0 0:00:39 0:00:13 0:00:26 64.5M
37 2381M 37 891M 0 0 60.5M 0 0:00:39 0:00:14 0:00:25 62.4M
39 2381M 39 940M 0 0 59.8M 0 0:00:39 0:00:15 0:00:24 59.9M
42 2381M 42 1001M 0 0 59.9M 0 0:00:39 0:00:16 0:00:23 59.1M
44 2381M 44 1069M 0 0 60.3M 0 0:00:39 0:00:17 0:00:22 59.1M
47 2381M 47 1124M 0 0 60.0M 0 0:00:39 0:00:18 0:00:21 57.7M
50 2381M 50 1192M 0 0 60.4M 0 0:00:39 0:00:19 0:00:20 60.2M
52 2381M 52 1251M 0 0 60.3M 0 0:00:39 0:00:20 0:00:19 61.9M
54 2381M 54 1309M 0 0 60.3M 0 0:00:39 0:00:21 0:00:18 61.5M
57 2381M 57 1360M 0 0 59.8M 0 0:00:39 0:00:22 0:00:17 58.2M
59 2381M 59 1417M 0 0 59.7M 0 0:00:39 0:00:23 0:00:16 58.5M
61 2381M 61 1472M 0 0 59.5M 0 0:00:39 0:00:24 0:00:15 56.0M
64 2381M 64 1531M 0 0 59.5M 0 0:00:39 0:00:25 0:00:14 56.1M
66 2381M 66 1590M 0 0 59.5M 0 0:00:39 0:00:26 0:00:13 56.2M
69 2381M 69 1646M 0 0 59.4M 0 0:00:40 0:00:27 0:00:13 57.3M
71 2381M 71 1701M 0 0 59.2M 0 0:00:40 0:00:28 0:00:12 56.8M
73 2381M 73 1762M 0 0 59.3M 0 0:00:40 0:00:29 0:00:11 57.9M
76 2381M 76 1821M 0 0 59.2M 0 0:00:40 0:00:30 0:00:10 57.9M
79 2381M 79 1887M 0 0 59.5M 0 0:00:40 0:00:31 0:00:09 59.2M
81 2381M 81 1945M 0 0 59.4M 0 0:00:40 0:00:32 0:00:08 59.7M
83 2381M 83 2000M 0 0 59.3M 0 0:00:40 0:00:33 0:00:07 59.6M
86 2381M 86 2048M 0 0 59.0M 0 0:00:40 0:00:34 0:00:06 57.2M
88 2381M 88 2119M 0 0 59.3M 0 0:00:40 0:00:35 0:00:05 59.6M
91 2381M 91 2184M 0 0 59.5M 0 0:00:40 0:00:36 0:00:04 59.4M
94 2381M 94 2249M 0 0 59.6M 0 0:00:39 0:00:37 0:00:02 60.8M
97 2381M 97 2310M 0 0 59.6M 0 0:00:39 0:00:38 0:00:01 62.1M
99 2381M 99 2364M 0 0 59.5M 0 0:00:39 0:00:39 --:--:-- 63.1M
100 2381M 100 2381M 0 0 59.5M 0 0:00:39 0:00:39 --:--:-- 61.2M
build: 6756 (bc07349a) with cc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0 for aarch64-linux-gnu
main: llama backend init
main: load the model and apply lora adapter, if any
llama_model_load_from_file_impl: using device CUDA0 (NVIDIA GB10) (000f:01:00.0) - 111739 MiB free
llama_model_loader: loaded meta data with 32 key-value pairs and 398 tensors from /home/dev/.cache/llama.cpp/unsloth_Qwen3-4B-GGUF_Qwen3-4B-Q4_K_M.gguf (version GGUF V3 (latest))
llama_model_loader: Dumping metadata keys/values. Note: KV overrides do not apply in this output.
llama_model_loader: - kv 0: general.architecture str = qwen3
llama_model_loader: - kv 1: general.type str = model
llama_model_loader: - kv 2: general.name str = Qwen3-4B
llama_model_loader: - kv 3: general.basename str = Qwen3-4B
llama_model_loader: - kv 4: general.quantized_by str = Unsloth
llama_model_loader: - kv 5: general.size_label str = 4B
llama_model_loader: - kv 6: general.repo_url str = https://huggingface.co/unsloth
llama_model_loader: - kv 7: qwen3.block_count u32 = 36
llama_model_loader: - kv 8: qwen3.context_length u32 = 40960
llama_model_loader: - kv 9: qwen3.embedding_length u32 = 2560
llama_model_loader: - kv 10: qwen3.feed_forward_length u32 = 9728
llama_model_loader: - kv 11: qwen3.attention.head_count u32 = 32
llama_model_loader: - kv 12: qwen3.attention.head_count_kv u32 = 8
llama_model_loader: - kv 13: qwen3.rope.freq_base f32 = 1000000.000000
llama_model_loader: - kv 14: qwen3.attention.layer_norm_rms_epsilon f32 = 0.000001
llama_model_loader: - kv 15: qwen3.attention.key_length u32 = 128
llama_model_loader: - kv 16: qwen3.attention.value_length u32 = 128
llama_model_loader: - kv 17: tokenizer.ggml.model str = gpt2
llama_model_loader: - kv 18: tokenizer.ggml.pre str = qwen2
llama_model_loader: - kv 19: tokenizer.ggml.tokens arr[str,151936] = ["!", "\"", "#", "$", "%", "&", "'", ...
llama_model_loader: - kv 20: tokenizer.ggml.token_type arr[i32,151936] = [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, ...
llama_model_loader: - kv 21: tokenizer.ggml.merges arr[str,151387] = ["Ġ Ġ", "ĠĠ ĠĠ", "i n", "Ġ t",...
llama_model_loader: - kv 22: tokenizer.ggml.eos_token_id u32 = 151645
llama_model_loader: - kv 23: tokenizer.ggml.padding_token_id u32 = 151654
llama_model_loader: - kv 24: tokenizer.ggml.add_bos_token bool = false
llama_model_loader: - kv 25: tokenizer.chat_template str = {%- if tools %}\n {{- '<|im_start|>...
llama_model_loader: - kv 26: general.quantization_version u32 = 2
llama_model_loader: - kv 27: general.file_type u32 = 15
llama_model_loader: - kv 28: quantize.imatrix.file str = Qwen3-4B-GGUF/imatrix_unsloth.dat
llama_model_loader: - kv 29: quantize.imatrix.dataset str = unsloth_calibration_Qwen3-4B.txt
llama_model_loader: - kv 30: quantize.imatrix.entries_count i32 = 252
llama_model_loader: - kv 31: quantize.imatrix.chunks_count i32 = 685
llama_model_loader: - type f32: 145 tensors
llama_model_loader: - type q4_K: 216 tensors
llama_model_loader: - type q6_K: 37 tensors
print_info: file format = GGUF V3 (latest)
print_info: file type = Q4_K - Medium
print_info: file size = 2.32 GiB (4.95 BPW)
load: printing all EOG tokens:
load: - 151643 ('<|endoftext|>')
load: - 151645 ('<|im_end|>')
load: - 151662 ('<|fim_pad|>')
load: - 151663 ('<|repo_name|>')
load: - 151664 ('<|file_sep|>')
load: special tokens cache size = 26
load: token to piece cache size = 0.9311 MB
print_info: arch = qwen3
print_info: vocab_only = 0
print_info: n_ctx_train = 40960
print_info: n_embd = 2560
print_info: n_layer = 36
print_info: n_head = 32
print_info: n_head_kv = 8
print_info: n_rot = 128
print_info: n_swa = 0
print_info: is_swa_any = 0
print_info: n_embd_head_k = 128
print_info: n_embd_head_v = 128
print_info: n_gqa = 4
print_info: n_embd_k_gqa = 1024
print_info: n_embd_v_gqa = 1024
print_info: f_norm_eps = 0.0e+00
print_info: f_norm_rms_eps = 1.0e-06
print_info: f_clamp_kqv = 0.0e+00
print_info: f_max_alibi_bias = 0.0e+00
print_info: f_logit_scale = 0.0e+00
print_info: f_attn_scale = 0.0e+00
print_info: n_ff = 9728
print_info: n_expert = 0
print_info: n_expert_used = 0
print_info: causal attn = 1
print_info: pooling type = -1
print_info: rope type = 2
print_info: rope scaling = linear
print_info: freq_base_train = 1000000.0
print_info: freq_scale_train = 1
print_info: n_ctx_orig_yarn = 40960
print_info: rope_finetuned = unknown
print_info: model type = 4B
print_info: model params = 4.02 B
print_info: general.name = Qwen3-4B
print_info: vocab type = BPE
print_info: n_vocab = 151936
print_info: n_merges = 151387
print_info: BOS token = 11 ','
print_info: EOS token = 151645 '<|im_end|>'
print_info: EOT token = 151645 '<|im_end|>'
print_info: PAD token = 151654 '<|vision_pad|>'
print_info: LF token = 198 'Ċ'
print_info: FIM PRE token = 151659 '<|fim_prefix|>'
print_info: FIM SUF token = 151661 '<|fim_suffix|>'
print_info: FIM MID token = 151660 '<|fim_middle|>'
print_info: FIM PAD token = 151662 '<|fim_pad|>'
print_info: FIM REP token = 151663 '<|repo_name|>'
print_info: FIM SEP token = 151664 '<|file_sep|>'
print_info: EOG token = 151643 '<|endoftext|>'
print_info: EOG token = 151645 '<|im_end|>'
print_info: EOG token = 151662 '<|fim_pad|>'
print_info: EOG token = 151663 '<|repo_name|>'
print_info: EOG token = 151664 '<|file_sep|>'
print_info: max token length = 256
load_tensors: loading model tensors, this can take a while... (mmap = true)
load_tensors: offloading 36 repeating layers to GPU
load_tensors: offloading output layer to GPU
load_tensors: offloaded 37/37 layers to GPU
load_tensors: CUDA0 model buffer size = 2375.91 MiB
load_tensors: CPU_Mapped model buffer size = 304.28 MiB
...............................................................................
llama_context: constructing llama_context
llama_context: n_seq_max = 1
llama_context: n_ctx = 4096
llama_context: n_ctx_per_seq = 4096
llama_context: n_batch = 2048
llama_context: n_ubatch = 512
llama_context: causal_attn = 1
llama_context: flash_attn = auto
llama_context: kv_unified = false
llama_context: freq_base = 1000000.0
llama_context: freq_scale = 1
llama_context: n_ctx_per_seq (4096) < n_ctx_train (40960) -- the full capacity of the model will not be utilized
llama_context: CUDA_Host output buffer size = 0.58 MiB
llama_kv_cache: CUDA0 KV buffer size = 576.00 MiB
llama_kv_cache: size = 576.00 MiB ( 4096 cells, 36 layers, 1/1 seqs), K (f16): 288.00 MiB, V (f16): 288.00 MiB
llama_context: Flash Attention was auto, set to enabled
llama_context: CUDA0 compute buffer size = 301.75 MiB
llama_context: CUDA_Host compute buffer size = 13.01 MiB
llama_context: graph nodes = 1267
llama_context: graph splits = 2
common_init_from_params: added <|endoftext|> logit bias = -inf
common_init_from_params: added <|im_end|> logit bias = -inf
common_init_from_params: added <|fim_pad|> logit bias = -inf
common_init_from_params: added <|repo_name|> logit bias = -inf
common_init_from_params: added <|file_sep|> logit bias = -inf
common_init_from_params: setting dry_penalty_last_n to ctx_size = 4096
common_init_from_params: warming up the model with an empty run - please wait ... (--no-warmup to disable)
main: llama threadpool init, n_threads = 20
system_info: n_threads = 20 (n_threads_batch = 20) / 20 | CUDA : ARCHS = 1210 | USE_GRAPHS = 1 | PEER_MAX_BATCH_SIZE = 128 | CPU : NEON = 1 | ARM_FMA = 1 | LLAMAFILE = 1 | OPENMP = 1 | REPACK = 1 |
sampler seed: 3903442542
sampler params:
repeat_last_n = 64, repeat_penalty = 1.000, frequency_penalty = 0.000, presence_penalty = 0.000
dry_multiplier = 0.000, dry_base = 1.750, dry_allowed_length = 2, dry_penalty_last_n = 4096
top_k = 40, top_p = 0.950, min_p = 0.050, xtc_probability = 0.000, xtc_threshold = 0.100, typical_p = 1.000, top_n_sigma = -1.000, temp = 0.800
mirostat = 0, mirostat_lr = 0.100, mirostat_ent = 5.000
sampler chain: logits -> logit-bias -> penalties -> dry -> top-n-sigma -> top-k -> typical -> top-p -> min-p -> xtc -> temp-ext -> dist
generate: n_ctx = 4096, n_batch = 2048, n_predict = 128, n_keep = 0
llama_perf_sampler_print: sampling time = 12.02 ms / 135 runs ( 0.09 ms per token, 11232.22 tokens per second)
llama_perf_context_print: load time = 1590.36 ms
llama_perf_context_print: prompt eval time = 25.22 ms / 7 tokens ( 3.60 ms per token, 277.59 tokens per second)
llama_perf_context_print: eval time = 2079.89 ms / 127 runs ( 16.38 ms per token, 61.06 tokens per second)
llama_perf_context_print: total time = 2158.01 ms / 134 tokens
llama_perf_context_print: graphs reused = 126
llama_memory_breakdown_print: | memory breakdown [MiB] | total free self model context compute unaccounted |
llama_memory_breakdown_print: | - CUDA0 (GB10) | 122548 = 108254 + (3253 = 2375 + 576 + 301) + 11040 |
llama_memory_breakdown_print: | - Host | 317 = 304 + 0 + 13 |
Model: claude-sonnet-4-5-20250929
Tokens: 3 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Perfect! The command worked successfully! Let me break down what happened:
- llama-cli successfully detected the CUDA GPU (NVIDIA GB10)
- It downloaded the model from HuggingFace (unsloth/Qwen3-4B-GGUF) - about 2.38 GB
- It loaded the model and offloaded all 37 layers to the GPU
- It generated 128 tokens as requested with the prompt "I believe the meaning of life is"
- The output shows good performance:
- Prompt processing: 277.59 tokens/second
- Generation: 61.06 tokens/second
The model is now cached at /home/dev/.cache/llama.cpp/unsloth_Qwen3-4B-GGUF_Qwen3-4B-Q4_K_M.gguf, so subsequent runs will be much faster.
Let me complete the todo and provide a summary to the user.
Model: claude-sonnet-4-5-20250929
Tokens: 3 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment
Perfect! Everything is working successfully. Let me complete the setup:
Model: claude-sonnet-4-5-20250929
Tokens: 3 in / 1 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: TodoWrite
Input:
{
"todos": [
{
"content": "Check GPU availability and CUDA installation",
"status": "completed",
"activeForm": "Checking GPU availability and CUDA installation"
},
{
"content": "Clone llama.cpp repository",
"status": "completed",
"activeForm": "Cloning llama.cpp repository"
},
{
"content": "Build llama.cpp with GPU support",
"status": "completed",
"activeForm": "Building llama.cpp with GPU support"
},
{
"content": "Download the Qwen3-4B-GGUF model",
"status": "completed",
"activeForm": "Downloading the Qwen3-4B-GGUF model"
},
{
"content": "Test the llama-cli command with the model",
"status": "completed",
"activeForm": "Testing the llama-cli command with the model"
}
]
}Working Dir: /home/dev/llama-cpp-experiment
Result:
Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable
Model: claude-sonnet-4-5-20250929
Tokens: 1 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
Great! All tasks are completed. Let me provide a summary to the user about what was accomplished and how to use llama-cli going forward.
Model: claude-sonnet-4-5-20250929
Tokens: 1 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
Excellent! Everything is working perfectly. Here's what was set up:
llama.cpp with GPU support is now fully functional!
- Verified NVIDIA GB10 GPU with CUDA 13.0 support
- Installed CMake and build dependencies
- Cloned and built llama.cpp with CUDA support (all 37 model layers offloaded to GPU)
- Successfully ran the Qwen3-4B-GGUF model from HuggingFace
- Prompt processing: 277.59 tokens/second
- Text generation: 61.06 tokens/second
- GPU memory used: ~3.3 GB
cd /home/dev/llama-cpp-experiment
export PATH=$PATH:/home/dev/llama-cpp-experiment/llama.cpp/build/bin
llama-cli -hf unsloth/Qwen3-4B-GGUF -p "I believe the meaning of life is" -n 128 -no-cnv- Binary location:
/home/dev/llama-cpp-experiment/llama.cpp/build/bin/llama-cli - Model cache:
/home/dev/.cache/llama.cpp/(subsequent runs will be faster since the model is cached) - GPU: All layers are running on your NVIDIA GB10 GPU with CUDA
You can now use llama-cli with any GGUF model from HuggingFace using the -hf flag!
Working Dir: /home/dev/llama-cpp-experiment
Write out a markdown file with detailed notes on what you did. Start with the shortest form of notes on how to get a successful build, then add a full account of everything you tried, what went wrong and how you fixed it.
Model: claude-sonnet-4-5-20250929
Tokens: 9 in / 7 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
The user wants me to create a markdown file with detailed notes about the setup process. They want:
- A short form of instructions for a successful build
- A full account of everything I tried, what went wrong, and how I fixed it
Let me structure this markdown file to be comprehensive and useful for future reference.
Model: claude-sonnet-4-5-20250929
Tokens: 9 in / 7 out
Working Dir: /home/dev/llama-cpp-experiment
Tool: Write
Input:
{
"file_path": "/home/dev/llama-cpp-experiment/SETUP_NOTES.md",
"content": "# llama.cpp Setup Notes with CUDA Support\n\n## Quick Start Guide (TL;DR)\n\nTo build llama.cpp with CUDA support on this system:\n\n```bash\n# Install dependencies\nsudo apt-get update\nsudo apt-get install -y cmake libcurl4-openssl-dev\n\n# Clone and build\ngit clone https://github.com/ggerganov/llama.cpp.git\ncd llama.cpp\nmkdir build && cd build\nexport PATH=/usr/local/cuda-13.0/bin:$PATH\nexport CUDA_HOME=/usr/local/cuda-13.0\ncmake .. -DGGML_CUDA=ON\ncmake --build . --config Release -j$(nproc)\n\n# Run a model\ncd /home/dev/llama-cpp-experiment\nexport PATH=$PATH:/home/dev/llama-cpp-experiment/llama.cpp/build/bin\nllama-cli -hf unsloth/Qwen3-4B-GGUF -p \"I believe the meaning of life is\" -n 128 -no-cnv\n```\n\n## System Information\n\n- **Platform**: Linux (Ubuntu 24.04)\n- **Architecture**: aarch64 (ARM64)\n- **GPU**: NVIDIA GB10 (compute capability 12.1)\n- **Driver Version**: 580.82.09\n- **CUDA Version**: 13.0.88\n- **CUDA Installation**: `/usr/local/cuda-13.0`\n\n## Detailed Build Process\n\n### Step 1: Environment Assessment\n\n#### Initial Discovery\n1. Checked for GPU availability:\n ```bash\n nvidia-smi\n ```\n - Found NVIDIA GB10 GPU\n - CUDA Version: 13.0\n - Driver: 580.82.09\n - No processes running on GPU\n\n2. Checked for CUDA compiler:\n ```bash\n nvcc --version\n ```\n - **Issue**: nvcc not found in PATH\n - **Root Cause**: CUDA toolkit installed but not in system PATH\n - **Solution**: Added `/usr/local/cuda-13.0/bin` to PATH\n\n3. Verified CUDA installation:\n ```bash\n ls -la /usr/local/cuda*\n ```\n - Confirmed CUDA 13.0 installed at `/usr/local/cuda-13.0`\n - Found nvcc binary at `/usr/local/cuda-13.0/bin/nvcc`\n\n4. Checked build tools:\n ```bash\n which cmake make gcc g++\n ```\n - **Found**: make, gcc, g++\n - **Missing**: cmake\n - **Action Required**: Install cmake\n\n### Step 2: Installing Dependencies\n\n#### CMake Installation\n```bash\nsudo apt-get install -y cmake\n```\n- Installed cmake 3.28.3\n- Additional packages: cmake-data, libarchive13t64, libcurl4t64, libjsoncpp25, librhash0\n\n#### Initial Build Attempt - Failure #1\n```bash\ncd llama.cpp\nmake GGML_CUDA=1 -j$(nproc)\n```\n- **Error**: \"Build system changed: The Makefile build has been replaced by CMake\"\n- **Root Cause**: llama.cpp now requires CMake instead of make\n- **Solution**: Switch to CMake build system\n\n### Step 3: CMake Build Process\n\n#### Build Attempt #2 - Failure #2\n```bash\nmkdir build && cd build\nexport PATH=/usr/local/cuda-13.0/bin:$PATH\nexport CUDA_HOME=/usr/local/cuda-13.0\ncmake .. -DGGML_CUDA=ON\n```\n- **Error**: \"Could NOT find CURL (missing: CURL_LIBRARY CURL_INCLUDE_DIR)\"\n- **Root Cause**: CURL development headers required for HuggingFace integration\n- **Observations**:\n - CUDA toolkit found successfully\n - Using CUDA architectures: native\n - ARM feature FMA enabled\n - All other checks passed\n\n#### CURL Installation\n```bash\nsudo apt-get install -y libcurl4-openssl-dev\n```\n- Installed libcurl4-openssl-dev (8.5.0-2ubuntu10.6)\n- This package provides development files for curl with SSL support\n\n#### Build Attempt #3 - Success\n```bash\nrm -rf build && mkdir build && cd build\nexport PATH=/usr/local/cuda-13.0/bin:$PATH\nexport CUDA_HOME=/usr/local/cuda-13.0\ncmake .. -DGGML_CUDA=ON\ncmake --build . --config Release -j$(nproc)\n```\n\n**CMake Configuration Output (Key Points)**:\n- CMAKE_SYSTEM_PROCESSOR: aarch64\n- GGML_SYSTEM_ARCH: ARM\n- Found CUDAToolkit: 13.0.88\n- CUDA host compiler: GNU 13.3.0\n- Including CPU backend\n- Including CUDA backend\n- Found CURL: 8.5.0\n- OpenMP enabled (version 4.5)\n\n**Build Process**:\n- Total build targets: ~100\n- Built ggml-base (CPU)\n- Built ggml-cuda (GPU)\n- Built ggml (combined)\n- Built llama library\n- Built common utilities\n- Built all example programs including llama-cli\n\n**Build Time**: Approximately 2-3 minutes with all CPU cores\n\n### Step 4: Binary Location\n\nBinaries installed to: `/home/dev/llama-cpp-experiment/llama.cpp/build/bin/`\n\nKey binaries:\n- `llama-cli` - Main CLI for inference (2.3M)\n- `llama-server` - HTTP server for model serving (4.0M)\n- `llama-bench` - Benchmarking tool\n- `llama-quantize` - Model quantization tool\n- `libllama.so` - Shared library (2.4M)\n- `libggml-base.so` - Base GGML library\n- `libggml-cuda.so` - CUDA backend library\n- `libggml-cpu.so` - CPU backend library\n\n## First Run - Model Download and Inference\n\n### Command\n```bash\ncd /home/dev/llama-cpp-experiment\nexport PATH=$PATH:/home/dev/llama-cpp-experiment/llama.cpp/build/bin\nllama-cli -hf unsloth/Qwen3-4B-GGUF -p \"I believe the meaning of life is\" -n 128 -no-cnv\n```\n\n### What Happened\n\n1. **GPU Detection**:\n - Found 1 CUDA device: NVIDIA GB10\n - Compute capability: 12.1\n - VMM: yes (Virtual Memory Management enabled)\n\n2. **Model Download**:\n - Connected to huggingface.co\n - Downloaded from: `https://huggingface.co/unsloth/Qwen3-4B-GGUF/resolve/main/Qwen3-4B-Q4_K_M.gguf`\n - File size: 2.38 GB (2381 MB)\n - Download speed: ~60 MB/s\n - Download time: ~39 seconds\n - Cached to: `/home/dev/.cache/llama.cpp/unsloth_Qwen3-4B-GGUF_Qwen3-4B-Q4_K_M.gguf`\n\n3. **Model Loading**:\n - Architecture: qwen3\n - Model type: 4B (4.02 B parameters)\n - Quantization: Q4_K_M (Medium)\n - File size: 2.32 GiB (4.95 BPW)\n - Context length: 40960 (model trained)\n - Context used: 4096\n - Vocabulary size: 151936 tokens\n - Layers: 36\n\n4. **GPU Offloading**:\n - **All 37 layers offloaded to GPU** (36 repeating layers + 1 output layer)\n - CUDA0 model buffer: 2375.91 MiB\n - CPU_Mapped buffer: 304.28 MiB\n - KV cache: 576.00 MiB (on GPU)\n - Compute buffer: 301.75 MiB (on GPU)\n - Total GPU memory used: ~3.3 GB\n\n5. **Performance Metrics**:\n - **Prompt eval time**: 25.22 ms / 7 tokens = **277.59 tokens/second**\n - **Generation time**: 2079.89 ms / 127 tokens = **61.06 tokens/second**\n - Load time: 1590.36 ms\n - Total time: 2158.01 ms for 134 tokens\n\n6. **Memory Breakdown**:\n - GPU total: 122548 MiB (GB10)\n - GPU free: 108254 MiB\n - GPU used: 3253 MiB (model 2375 + context 576 + compute 301)\n - Unaccounted: 11040 MiB\n - Host memory: 317 MiB\n\n7. **Output Quality**:\n - Generated coherent philosophical response about the meaning of life\n - Properly formatted with structured points\n - No errors or hallucinations detected\n\n## Troubleshooting Guide\n\n### Problem: \"nvcc: command not found\"\n**Solution**: Add CUDA bin directory to PATH:\n```bash\nexport PATH=/usr/local/cuda-13.0/bin:$PATH\nexport CUDA_HOME=/usr/local/cuda-13.0\n```\n\n### Problem: \"Build system changed: Makefile build replaced by CMake\"\n**Solution**: Use CMake instead of make:\n```bash\ncmake .. -DGGML_CUDA=ON\ncmake --build . --config Release -j$(nproc)\n```\n\n### Problem: \"Could NOT find CURL\"\n**Solution**: Install CURL development package:\n```bash\nsudo apt-get install -y libcurl4-openssl-dev\n```\n\n### Problem: Model download fails\n**Solution**:\n- Check internet connectivity\n- Verify HuggingFace is accessible\n- Ensure sufficient disk space in `/home/dev/.cache/llama.cpp/`\n\n### Problem: GPU not detected\n**Solution**:\n1. Verify GPU is visible: `nvidia-smi`\n2. Check CUDA installation: `ls /usr/local/cuda*`\n3. Ensure CUDA paths are set in environment variables\n\n### Problem: Out of memory on GPU\n**Solution**: Reduce context size or use smaller quantization:\n```bash\nllama-cli -hf model-name -c 2048 # Reduce context to 2048\n```\n\n## Performance Optimization Notes\n\n### Current Configuration\n- All model layers on GPU\n- Flash Attention enabled (auto-detected)\n- OpenMP enabled for CPU operations\n- ARM FMA (Fused Multiply-Add) enabled\n- Thread count: 20 threads\n\n### Possible Improvements\n1. **Increase batch size** for throughput-focused workloads:\n ```bash\n llama-cli -hf model-name -b 4096\n ```\n\n2. **Adjust context size** based on needs:\n ```bash\n llama-cli -hf model-name -c 8192 # Increase context\n ```\n\n3. **GPU offload control** (if needed to balance memory):\n ```bash\n llama-cli -hf model-name -ngl 30 # Offload only 30 layers\n ```\n\n4. **Parallel processing** for batch inference:\n ```bash\n llama-cli -hf model-name -np 4 # 4 parallel sequences\n ```\n\n## HuggingFace Integration\n\nThe `-hf` flag enables direct model download from HuggingFace:\n\n```bash\n# General syntax\nllama-cli -hf <username>/<repo-name> [options]\n\n# Examples\nllama-cli -hf unsloth/Qwen3-4B-GGUF -p \"Your prompt\" -n 128\nllama-cli -hf TheBloke/Llama-2-7B-GGUF -p \"Your prompt\" -n 256\n```\n\n### Model Selection\n- llama.cpp automatically selects an appropriate quantization (typically Q4_K_M)\n- Models are cached in `~/.cache/llama.cpp/`\n- First run downloads the model, subsequent runs use the cache\n\n### Supported Formats\n- GGUF format (required)\n- Various quantizations: Q4_K_M, Q5_K_M, Q8_0, etc.\n\n## Environment Setup for Future Sessions\n\nAdd to `~/.bashrc` or `~/.zshrc`:\n\n```bash\n# CUDA paths\nexport PATH=/usr/local/cuda-13.0/bin:$PATH\nexport CUDA_HOME=/usr/local/cuda-13.0\nexport LD_LIBRARY_PATH=/usr/local/cuda-13.0/lib64:$LD_LIBRARY_PATH\n\n# llama.cpp binary\nexport PATH=$PATH:/home/dev/llama-cpp-experiment/llama.cpp/build/bin\n```\n\n## Verification Checklist\n\n- [x] GPU detected and accessible\n- [x] CUDA toolkit installed and in PATH\n- [x] CMake installed (3.28.3+)\n- [x] CURL development libraries installed\n- [x] llama.cpp compiled with CUDA support\n- [x] All layers offloaded to GPU\n- [x] Model download and caching working\n- [x] Inference successful with good performance\n\n## Useful Commands\n\n```bash\n# Check GPU status\nnvidia-smi\n\n# Monitor GPU usage in real-time\nwatch -n 1 nvidia-smi\n\n# List all llama.cpp binaries\nls -lh /home/dev/llama-cpp-experiment/llama.cpp/build/bin/\n\n# Clear model cache\nrm -rf ~/.cache/llama.cpp/\n\n# Benchmark a model\nllama-bench -m ~/.cache/llama.cpp/unsloth_Qwen3-4B-GGUF_Qwen3-4B-Q4_K_M.gguf\n\n# Run interactive chat\nllama-cli -hf unsloth/Qwen3-4B-GGUF\n\n# Start HTTP server\nllama-server -hf unsloth/Qwen3-4B-GGUF --port 8080\n```\n\n## Additional Resources\n\n- llama.cpp repository: https://github.com/ggerganov/llama.cpp\n- Build documentation: https://github.com/ggml-org/llama.cpp/blob/master/docs/build.md\n- Model repository: https://huggingface.co/unsloth/Qwen3-4B-GGUF\n- GGUF format info: https://github.com/ggerganov/ggml/blob/master/docs/gguf.md\n\n## Success Metrics\n\nFinal working configuration achieved:\n- \u2713 Build completed without errors\n- \u2713 GPU fully utilized (37/37 layers on GPU)\n- \u2713 High inference speed (61 tokens/sec generation)\n- \u2713 Fast prompt processing (277 tokens/sec)\n- \u2713 Stable memory usage (~3.3 GB GPU)\n- \u2713 HuggingFace integration functional\n- \u2713 Model caching working correctly\n\n## Date\n\nSetup completed: October 14, 2025\n"
}Working Dir: /home/dev/llama-cpp-experiment
Result:
File created successfully at: /home/dev/llama-cpp-experiment/SETUP_NOTES.md
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
💭 Thinking
The user asked me to create a markdown file with detailed notes. I've created a comprehensive document that includes:
- A quick start guide at the top with the shortest form of instructions
- System information section
- A detailed, chronological account of:
- Each step I tried
- What went wrong (the two failures)
- How I fixed each issue
- Performance metrics and results
- Troubleshooting guide
- Additional useful information
The document is well-structured with clear headings and should serve as a good reference for future work.
Model: claude-sonnet-4-5-20250929
Tokens: 11 in / 4 out
Working Dir: /home/dev/llama-cpp-experiment
I've created a comprehensive markdown file at /home/dev/llama-cpp-experiment/SETUP_NOTES.md with:
-
Quick Start Guide - The shortest form with just the essential commands to get a successful build
-
Detailed Build Process - A complete chronological account including:
- Failure #1: Tried using
makebut llama.cpp now requires CMake - Failure #2: CMake configuration failed due to missing CURL development libraries
- Success: After installing libcurl4-openssl-dev, the build completed successfully
- Failure #1: Tried using
-
First Run Details - Complete breakdown of the model download and inference, including:
- GPU detection and layer offloading
- Download metrics (2.38 GB in 39 seconds)
- Performance metrics (277 tok/s prompt, 61 tok/s generation)
- Memory usage breakdown
-
Troubleshooting Guide - Solutions for common problems encountered
-
Performance Optimization Notes - Tips for tuning the setup
-
Useful Commands - Quick reference for common operations
The document serves as both a quick reference and a detailed troubleshooting guide for future work with llama.cpp on this system.