This is a fork of llama.cpp tuned for two Tesla P100s (sm_60). On Qwen3.8-27B, plain decode runs at 1.86x upstream's speed (17.5 -> 32.6 t/s), and ~3x with the model's built-in MTP head (~54 t/s). Prefill runs at ~2x (250 -> 493 t/s at short context). The full 262k window fits with vision loaded, and a question on a full 260k context prefills at ~153 t/s. The math is at least as accurate as stock: KLD against an fp32 run 0.00119, where upstream's fp16 path reads 0.00152. It tracks upstream by merging. See p100-docs/ for results, changes and how to run it. Upstream's README follows.
LLM inference in C/C++
ggml / ops / maintainer PRs / dev stats / lib llama API / llama-server REST API
A few options to get llama.cpp installed on your machine:
- Visit https://llama.app and follow the instructions
- Run with Docker - see our Docker documentation
- Download pre-built binaries from the releases page
- Build from source by cloning this repository - check out our build guide
Once installed:
llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF
llama serve -hf ggml-org/Qwen3.5-0.8B-GGUF
| VLM session with llama cli | Built-in web UI against llama serve |
The main goal of llama.cpp is to enable LLM (and VLM) inference with minimal setup and state-of-the-art performance on
a wide range of hardware - locally and in the cloud.
- Plain C/C++ implementation without any dependencies
- Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks
- AVX, AVX2, AVX512 and AMX support for x86 architectures
- RVV, ZVFH, ZFH, ZICBOP and ZIHINT support for RISC-V architectures
- 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use
- Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads GPUs via MUSA)
- Vulkan and SYCL backend support
- CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
The llama.cpp project is build on top of the ggml library.
| Backend | Target devices |
|---|---|
| BLAS | All |
| BLIS | All |
| CANN | Ascend NPU |
| CUDA | Nvidia GPU |
| HIP | AMD GPU |
| Hexagon | Snapdragon |
| IBM zDNN | IBM Z & LinuxONE |
| MUSA | Moore Threads GPU |
| Metal | Apple Silicon |
| OpenCL | Adreno GPU |
| OpenVINO [In Progress] | Intel CPUs, GPUs, and NPUs |
| RPC | All |
| SYCL | Intel GPU |
| VirtGPU | VirtGPU APIR |
| Vulkan | GPU |
| WebGPU | All |
| ZenDNN | AMD CPU |
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Contributors can open PRs
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Collaborators will be invited based on contributions
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Maintainers can push to branches in the
llama.cpprepo and merge PRs into themasterbranch -
Any help with managing issues, PRs and projects is very appreciated!
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Read the CONTRIBUTING.md for more information
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yhirose/cpp-httplib - Single-header HTTP server, used by
llama-server- MIT license -
nothings/stb - Single-header image format decoder, used by multimodal subsystem - Public domain
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nlohmann/json - Single-header JSON library, used by various tools/examples - MIT License
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mackron/miniaudio - Single-header audio format decoder, used by multimodal subsystem - Public domain
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sheredom/subprocess.h - Single-header process launching solution for C and C++ - Public domain