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Docs: consolidate build-from-source and GPU backend guide

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Assessment

Difficulty
2/5
Estimated time
1-3 hours
Newbie friendliness
75/100
Issue type
Documentation
Clarity
Clearly specified
Activity status
Quiet
Tech stack
cmake, python

Research direction

The issue points to consolidating build documentation, likely in docs/build.md or a new docs/gpu.md. Start by reviewing the existing README, CONTRIBUTING.md, and the linked GitHub issues (#2013, #695, #721, #756) to understand the current scattered information. Then, create a clear table of CMAKE_ARGS for each GPU backend and add troubleshooting steps for common errors. Verify the changes by building the project with a GPU backend to ensure the instructions work.

Written by the indexing model from the issue text.

Description

Problem

The build-from-source documentation is spread across README, CONTRIBUTING.md, and many GitHub issues (e.g. #2013, #695, #721, #756). Users with newer GPUs (RTX 50-series, sm_120) or uncommon CUDA versions repeatedly hit the same build failures because the docs lack:

  1. A CMAKE_ARGS mapping table showing which flag to set for each GPU backend
  2. CUDA version compatibility notes (e.g., CUDA 12.9+ requires specific cmake workarounds)
  3. The minimum/maximum supported CUDA toolkit versions
  4. How to verify the build actually used the GPU (simple Python snippet to check backend)

Suggested improvements

In docs/build.md (or a new docs/gpu.md):

| Backend | CMAKE_ARGS                                    | GPU Requirements              |
|---------|-----------------------------------------------|-------------------------------|
| CUDA    | -DGGML_CUDA=ON                                | NVIDIA GPU, CUDA >= 11.3      |
| Metal   | -DGGML_METAL=ON (default on macOS)            | Apple Silicon or AMD GPU      |
| Vulkan  | -DGGML_VULKAN=ON                              | Vulkan 1.2+ capable GPU       |
| SYCL    | -DGGML_SYCL=ON -DGGML_SYCL_TARGET=INTEL       | Intel Arc / Iris Xe           |
| HIP     | -DGGML_HIPBLAS=ON                             | AMD ROCm-compatible GPU       |

And a troubleshooting section for the most common build errors (CMake not finding CUDA, nvcc version mismatch, sm_120 not recognized).

Value

Consolidating this reduces the "can't install with GPU" issues that currently fill the tracker.

Dominant language
Python
Stars
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Forks
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Avg merge
6h 43m
Merged PRs (30d)
2

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First steps

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  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

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