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README.md
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README.md
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## TL;DR
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## TL;DR
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This repository is a fork of [llama.cpp](https://github.com/ggerganov/llama.cpp) with better CPU and hybrid GPU/CPU performance.
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This repository is a fork of [llama.cpp](https://github.com/ggerganov/llama.cpp) with better CPU and hybrid GPU/CPU performance, new SOTA quantization types, first-class Bitnet support, better DeepSeek performance via MLA, FlashMLA, fused MoE operations and tensor overrides for hybrid GPU/CPU inference, row-interleaved quant packing, etc.
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## Latest News
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## Latest News
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* Feb 9 2025: MLA for DeepSeek models
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* Feb 9 2025: MLA for DeepSeek models
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* Jan 23 2025: DeepSeek-V3 support added
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* Jan 23 2025: DeepSeek-V3 support added
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### Contributing
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## Resources
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Contributions in form of pull requests or issue submissions (bug reports, feature requests) are welcome.
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There is no single point of reference describing all new `ik_llama.cpp` features. Pull requests often contain detailed information, so browsing the PRs is often the best way to learn about new features and how to use them. In addition
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* [The Wiki page](https://github.com/ikawrakow/ik_llama.cpp/wiki) has performance comparisons to mainline `llama.cpp`
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* [This guide](https://github.com/ikawrakow/ik_llama.cpp/discussions/258) is a good place to start if you came here because of DeepSeek models
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* [This discussion](https://github.com/ikawrakow/ik_llama.cpp/discussions/266) is about running DeepSeek-V3/R1 on a 16 x 3090 setup
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* [This discussion](https://github.com/ikawrakow/ik_llama.cpp/discussions/8) describes the new quantization types available in `ik_llama.cpp`
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### Licens
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## Contributing
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Contributions in form of pull requests, issue submissions (bug reports, feature requests), or general discussions, are welcome.
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## License
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MIT
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MIT
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