Today's LLM & Language Models: Fastest-Growing Projects — May 07, 2026
This week, the LLM & Language Models space saw significant growth in tools focused on optimizing and fine-tuning large language models. We observed a surge in repositories that provide benchmarks for evaluating LLMs, as well as projects that aim to make these models more accessible and user-friendly. Additionally, there was a notable interest in tools that enable the development of more specialized language models.
youssofal/MTPLX (Growth Score: 69.60, Stars: 177) is a repository that provides native MTP speculative decoding on Apple Silicon, resulting in a 2x-2.5x decode TPS increase at temperature 0.6. Its growth can be attributed to its compatibility with OpenAI API and Anthropic, making it an attractive solution for developers looking to optimize their LLMs.
openai/privacy-filter (Growth Score: 62.90, Stars: 1,979) is a repository that houses the OpenAI Privacy Filter, which likely contributes to its high growth score despite having only three commits in the past month. Its popularity can be attributed to the increasing importance of data privacy and security in the development of LLMs.
DestinyLinker/MingLi-Bench (Growth Score: 38.33, Stars: 760) is a benchmark for evaluating LLMs on Chinese traditional fortune telling — Bazi (八字) and Ziwei Doushu (紫微斗数). Its growth can be attributed to the growing interest in developing more specialized language models that cater to specific cultural or linguistic contexts.
jingyaogong/minimind-o (Growth Score: 38.17, Stars: 329) is a repository that provides a 0.1B Omni model trained from scratch, capable of listening, speaking, and seeing. Its growth can be attributed to its versatility and potential for applications in various areas such as customer service or content creation.
hexiecs/talk-normal (Growth Score: 36.24, Stars: 1,601) is a system prompt that removes AI slop from LLMs, making them talk like normal people. Its growth can be attributed to the increasing demand for more human-like interactions with language models.
Beever-AI/beever-atlas (Growth Score: 30.19, Stars: 261) provides a knowledge base for LLM-Wiki conversations. Its growth can be attributed to its potential for enabling more informed and accurate responses from language models.
AlexCheema/talos-vs-macbook (Growth Score: 27.70, Stars: 154) is a repository that benchmarks microGPT on an M4 Max MacBook Pro P-core against TALOS-V2's FPGA implementation. Its growth can be attributed to the increasing interest in evaluating and optimizing LLMs for various hardware configurations.
amitshekhariitbhu/llm-internals (Growth Score: 25.82, Stars: 967) provides a step-by-step guide to learning LLM internals. Its growth can be attributed to its educational value and the increasing interest in understanding how LLMs work.
JackLuguibin/OpenPawlet (Growth Score: 21.39, Stars: 102) is a single-process web console for the OpenPawlet ecosystem. Although it has a lower growth score compared to other repositories on this list, its growth can be attributed to its potential for enabling more accessible and user-friendly interactions with language models.
Lastly, skyllwt/OmegaWiki (Growth Score: 20.82, Stars: 542) is a wiki-centric full-lifecycle AI research platform powered by Claude Code. Its growth can be attributed to its comprehensive approach to LLM development and the increasing interest in more integrated solutions for AI research.
youssofal/MTPLX (Growth Score: 69.60, Stars: 177) is a repository that provides native MTP speculative decoding on Apple Silicon, resulting in a 2x-2.5x decode TPS increase at temperature 0.6. Its growth can be attributed to its compatibility with OpenAI API and Anthropic, making it an attractive solution for developers looking to optimize their LLMs.
openai/privacy-filter (Growth Score: 62.90, Stars: 1,979) is a repository that houses the OpenAI Privacy Filter, which likely contributes to its high growth score despite having only three commits in the past month. Its popularity can be attributed to the increasing importance of data privacy and security in the development of LLMs.
DestinyLinker/MingLi-Bench (Growth Score: 38.33, Stars: 760) is a benchmark for evaluating LLMs on Chinese traditional fortune telling — Bazi (八字) and Ziwei Doushu (紫微斗数). Its growth can be attributed to the growing interest in developing more specialized language models that cater to specific cultural or linguistic contexts.
jingyaogong/minimind-o (Growth Score: 38.17, Stars: 329) is a repository that provides a 0.1B Omni model trained from scratch, capable of listening, speaking, and seeing. Its growth can be attributed to its versatility and potential for applications in various areas such as customer service or content creation.
hexiecs/talk-normal (Growth Score: 36.24, Stars: 1,601) is a system prompt that removes AI slop from LLMs, making them talk like normal people. Its growth can be attributed to the increasing demand for more human-like interactions with language models.
Beever-AI/beever-atlas (Growth Score: 30.19, Stars: 261) provides a knowledge base for LLM-Wiki conversations. Its growth can be attributed to its potential for enabling more informed and accurate responses from language models.
AlexCheema/talos-vs-macbook (Growth Score: 27.70, Stars: 154) is a repository that benchmarks microGPT on an M4 Max MacBook Pro P-core against TALOS-V2's FPGA implementation. Its growth can be attributed to the increasing interest in evaluating and optimizing LLMs for various hardware configurations.
amitshekhariitbhu/llm-internals (Growth Score: 25.82, Stars: 967) provides a step-by-step guide to learning LLM internals. Its growth can be attributed to its educational value and the increasing interest in understanding how LLMs work.
JackLuguibin/OpenPawlet (Growth Score: 21.39, Stars: 102) is a single-process web console for the OpenPawlet ecosystem. Although it has a lower growth score compared to other repositories on this list, its growth can be attributed to its potential for enabling more accessible and user-friendly interactions with language models.
Lastly, skyllwt/OmegaWiki (Growth Score: 20.82, Stars: 542) is a wiki-centric full-lifecycle AI research platform powered by Claude Code. Its growth can be attributed to its comprehensive approach to LLM development and the increasing interest in more integrated solutions for AI research.