Today's LLM & Language Models: Fastest-Growing Projects — May 09, 2026
Today's the LLM & Language Models space, we're seeing a surge of interest in tools that enhance or interact with large language models, such as those from OpenAI and Anthropic. Developers are creating innovative solutions to improve performance, accessibility, and functionality, driving growth in this category. From optimized decoding to knowledge compilation engines, these tools are pushing the boundaries of what's possible with LLMs.
youssofal/MTPLX (Growth Score: 63.07, Stars: 250) is a notable example, offering native MTP speculative decoding on Apple Silicon that can increase decode TPS by 2-2.5x at temperature 0.6. Its growth is likely due to its impressive performance improvements and compatibility with OpenAI API/Anthropic-compatible serving.
openai/privacy-filter (Growth Score: 58.77, Stars: 2034) has also seen significant attention, despite only three commits in the past month. As an official OpenAI project, this tool provides a robust solution for filtering sensitive information, which is likely driving its growth and popularity among developers.
jingyaogong/minimind-o (Growth Score: 55.31, Stars: 636) is another standout, offering a 0.1B Omni model trained from scratch that can listen, speak, and see. Its growth may be attributed to the novelty of this all-modality approach, which could enable more sophisticated applications in areas like conversational AI.
DestinyLinker/MingLi-Bench (Growth Score: 41.24, Stars: 922) provides a benchmark for evaluating LLMs on Chinese traditional fortune telling, filling a specific niche in the market. Its growth score and number of stars suggest that this tool is gaining traction among developers interested in cultural applications.
Beever-AI/beever-atlas (Growth Score: 27.19, Stars: 271) offers an innovative approach to knowledge management with its LLM-wiki conversation knowledge base. With 100 commits in the past month, it's clear that this project is actively being developed and refined, which may be driving interest among potential users.
amitshekhariitbhu/llm-internals (Growth Score: 24.07, Stars: 973) provides a comprehensive guide to understanding LLM internals, from tokenization to attention to inference optimization. Its growth is likely due to the educational value it offers, making it an essential resource for developers seeking to improve their skills.
Several other projects are also worth mentioning, including AlexCheema/talos-vs-macbook (Growth Score: 19.93), which provides microGPT benchmarks comparing a MacBook Pro P-core with TALOS-V2's FPGA implementation, and JackLuguibin/OpenPawlet (Growth Score: 19.36), which offers an open-source web console for the OpenPawlet ecosystem.
Lastly, axoviq-ai/synthadoc (Growth Score: 17.02) is a knowledge compilation engine that turns raw documents into structured wikis, and chiefautism/privacy-parser (Growth Score: 15.56) provides an alternative to traditional RAG by returning PII as structured spans instead of masking. Both projects demonstrate the creative ways developers are using LLMs to solve real-world problems.
youssofal/MTPLX (Growth Score: 63.07, Stars: 250) is a notable example, offering native MTP speculative decoding on Apple Silicon that can increase decode TPS by 2-2.5x at temperature 0.6. Its growth is likely due to its impressive performance improvements and compatibility with OpenAI API/Anthropic-compatible serving.
openai/privacy-filter (Growth Score: 58.77, Stars: 2034) has also seen significant attention, despite only three commits in the past month. As an official OpenAI project, this tool provides a robust solution for filtering sensitive information, which is likely driving its growth and popularity among developers.
jingyaogong/minimind-o (Growth Score: 55.31, Stars: 636) is another standout, offering a 0.1B Omni model trained from scratch that can listen, speak, and see. Its growth may be attributed to the novelty of this all-modality approach, which could enable more sophisticated applications in areas like conversational AI.
DestinyLinker/MingLi-Bench (Growth Score: 41.24, Stars: 922) provides a benchmark for evaluating LLMs on Chinese traditional fortune telling, filling a specific niche in the market. Its growth score and number of stars suggest that this tool is gaining traction among developers interested in cultural applications.
Beever-AI/beever-atlas (Growth Score: 27.19, Stars: 271) offers an innovative approach to knowledge management with its LLM-wiki conversation knowledge base. With 100 commits in the past month, it's clear that this project is actively being developed and refined, which may be driving interest among potential users.
amitshekhariitbhu/llm-internals (Growth Score: 24.07, Stars: 973) provides a comprehensive guide to understanding LLM internals, from tokenization to attention to inference optimization. Its growth is likely due to the educational value it offers, making it an essential resource for developers seeking to improve their skills.
Several other projects are also worth mentioning, including AlexCheema/talos-vs-macbook (Growth Score: 19.93), which provides microGPT benchmarks comparing a MacBook Pro P-core with TALOS-V2's FPGA implementation, and JackLuguibin/OpenPawlet (Growth Score: 19.36), which offers an open-source web console for the OpenPawlet ecosystem.
Lastly, axoviq-ai/synthadoc (Growth Score: 17.02) is a knowledge compilation engine that turns raw documents into structured wikis, and chiefautism/privacy-parser (Growth Score: 15.56) provides an alternative to traditional RAG by returning PII as structured spans instead of masking. Both projects demonstrate the creative ways developers are using LLMs to solve real-world problems.