LLM inference in C/C++
ggml / ops / maintainer PRs / dev stats / lib llama API / llama-server REST API
A community fork of llama.cpp optimized for Poolside Laguna S 2.1 (Q4_K_XL, Q5_K_XL), Qwen3.8 Flash Next (Q4_K_XL), Qwen 3.6 35B A3B (Q8_K_XL, Q4_K_XL), and other models. stable is the current stable variant; unstable contains our latest changes; master tracks upstream.
What this fork adds on top of upstream:
| Change | Flag | What it does |
|---|---|---|
| Adaptive speculative draft length | --spec-draft-adaptive |
Sizes each draft from a measured per-sequence acceptance EMA instead of always drafting --spec-draft-n-max; improves throughput across content types without changing output |
| Higher-precision embedding tables | --ple FILE |
Loads per-layer embedding (PLE) tables from a sidecar GGUF, replacing the lookup tables of the same name in the model file |
| Qwen3.8-Flash-Next MTP draft head | -md / --model-draft |
Integrates the model's MTP head with the hybrid-idx KV cache memory and graph fusion for multi-token draft proposals |
| Laguna S 2.1 support | DFlash-based draft model integration with shared embedding contexts, target-layer extraction, and f16-activation overflow sanitization on Metal | |
| Vulkan FA for q4_0/q4_1/q5_0/q5_1 | Extends the dequant-once flash attention scratch path to common 4–5-bit quant types, not just Q8_0 | |
| AMD coopmat tuning | f16-B matmul auto-mode for RDNA3, density-aware vec-vs-coopmat dispatch, int8 quantized matmul shaders, deterministic top-K radix select | |
| UMA-aware memory gating | common/host-ram.cpp queries available RAM to gate FA scratch allocation on APUs and hybrid GPU systems |
A few options to get llama.cpp installed on your machine:
# curl
curl -LsSf https://llama.app/install.sh | sh
# powershell
irm https://llama.app/install.ps1 | iex- 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:
# Download and run a model directly from Hugging Face
llama cli -hf ggml-org/Qwen3.5-0.8B-GGUF
# Launch OpenAI-compatible API server
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 ZIHINTPAUSE 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 |
- How to build
- Running on Docker
- Build on Android
- Multi-GPU usage
- Performance troubleshooting
- GGML tips & tricks
- XCFramework
- Completions
- Models
- Release process
- Contributors can open PRs
- Collaborators will be invited based on contributions
- 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!
- Read the CONTRIBUTING.md for more information
- 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
- nlohmann/json - Single-header JSON library, used by various tools/examples - MIT License
- mackron/miniaudio - Single-header audio format decoder, used by multimodal subsystem - Public domain
- sheredom/subprocess.h - Single-header process launching solution for C and C++ - Public domain