Today's LLM & Language Models: Fastest-Growing Projects — May 06, 2026
Today's the LLM & Language Models space, we've seen a surge in innovative projects that aim to improve the efficiency, accessibility, and usability of large language models. From native speculative decoding on Apple Silicon to making LLMs talk like normal people, developers are pushing the boundaries of what's possible with these powerful tools.
youssofal/MTPLX, with a growth score of 71.88 and 104 stars, has seen significant traction for its native MTP speculative decoding on Apple Silicon, resulting in a 2x-2.5x decode TPS increase at temperature 0.6. Its compatibility with OpenAI API and Anthropic-compatible serving makes it an attractive solution for developers looking to optimize their LLM workflows.
openai/privacy-filter boasts an impressive 1,951 stars and a growth score of 65.32, likely due to its straightforward yet critical function as an OpenAI Privacy Filter. Although commit activity has been relatively low in the past month, the repository's popularity suggests that developers are taking data protection seriously when working with LLMs.
hexiecs/talk-normal has gained significant attention with 1,587 stars and a growth score of 37.29, offering a system prompt that removes AI slop from LLM output, making it sound more like human-like conversation. This tool's popularity highlights the growing interest in creating more natural-sounding language models.
AlexCheema/talos-vs-macbook, with a growth score of 34.00 and 152 stars, presents an intriguing benchmark comparison between a MacBook Pro P-core and TALOS-V2's FPGA implementation, showcasing the former's impressive performance. This repository's growing interest likely stems from developers seeking to optimize their hardware choices for LLM workloads.
Beever-AI/beever-atlas has garnered 255 stars and a growth score of 31.80 for its innovative approach to creating a knowledge base using LLM-Wiki conversations. The project's active development, with 100 commits in the past month, suggests that developers are eager to explore new ways to leverage LLMs for knowledge management.
amitshekhariitbhu/llm-internals offers a comprehensive guide to learning LLM internals, covering topics from tokenization to attention and inference optimization. With 959 stars and a growth score of 26.60, this repository is likely attracting developers seeking a deeper understanding of how LLMs work.
JackLuguibin/OpenPawlet has seen significant activity with 100 commits in the past month, earning it a growth score of 22.58 and 102 stars. This single-process web console for the OpenPawlet ecosystem provides an HTTP API, browser UI, and embedded agent runtime, making it an attractive choice for developers building LLM-powered applications.
skyllwt/OmegaWiki has gained traction with 498 stars and a growth score of 20.33, offering a fully realized version of Karpathy's LLM-Wiki vision as a wiki-centric full-lifecycle AI research platform powered by Claude Code. The repository's popularity suggests that developers are interested in exploring new ways to integrate LLMs into their workflows.
chiefautism/privacy-parser offers an interesting reversal of the OpenAI Privacy Filter, returning PII as structured spans instead of masking. With 393 stars and a growth score of 19.15, this repository likely appeals to developers seeking more nuanced approaches to data protection.
kytmanov/obsidian-llm-wiki-local has attracted attention with 490 stars and a growth score of 16.78 for its implementation of Karpathy’s LLM Wiki using Ollama, allowing users to create a local wiki that auto-links and grows without sharing notes. This repository's popularity highlights the growing interest in creating more private and secure LLM-powered tools.
youssofal/MTPLX, with a growth score of 71.88 and 104 stars, has seen significant traction for its native MTP speculative decoding on Apple Silicon, resulting in a 2x-2.5x decode TPS increase at temperature 0.6. Its compatibility with OpenAI API and Anthropic-compatible serving makes it an attractive solution for developers looking to optimize their LLM workflows.
openai/privacy-filter boasts an impressive 1,951 stars and a growth score of 65.32, likely due to its straightforward yet critical function as an OpenAI Privacy Filter. Although commit activity has been relatively low in the past month, the repository's popularity suggests that developers are taking data protection seriously when working with LLMs.
hexiecs/talk-normal has gained significant attention with 1,587 stars and a growth score of 37.29, offering a system prompt that removes AI slop from LLM output, making it sound more like human-like conversation. This tool's popularity highlights the growing interest in creating more natural-sounding language models.
AlexCheema/talos-vs-macbook, with a growth score of 34.00 and 152 stars, presents an intriguing benchmark comparison between a MacBook Pro P-core and TALOS-V2's FPGA implementation, showcasing the former's impressive performance. This repository's growing interest likely stems from developers seeking to optimize their hardware choices for LLM workloads.
Beever-AI/beever-atlas has garnered 255 stars and a growth score of 31.80 for its innovative approach to creating a knowledge base using LLM-Wiki conversations. The project's active development, with 100 commits in the past month, suggests that developers are eager to explore new ways to leverage LLMs for knowledge management.
amitshekhariitbhu/llm-internals offers a comprehensive guide to learning LLM internals, covering topics from tokenization to attention and inference optimization. With 959 stars and a growth score of 26.60, this repository is likely attracting developers seeking a deeper understanding of how LLMs work.
JackLuguibin/OpenPawlet has seen significant activity with 100 commits in the past month, earning it a growth score of 22.58 and 102 stars. This single-process web console for the OpenPawlet ecosystem provides an HTTP API, browser UI, and embedded agent runtime, making it an attractive choice for developers building LLM-powered applications.
skyllwt/OmegaWiki has gained traction with 498 stars and a growth score of 20.33, offering a fully realized version of Karpathy's LLM-Wiki vision as a wiki-centric full-lifecycle AI research platform powered by Claude Code. The repository's popularity suggests that developers are interested in exploring new ways to integrate LLMs into their workflows.
chiefautism/privacy-parser offers an interesting reversal of the OpenAI Privacy Filter, returning PII as structured spans instead of masking. With 393 stars and a growth score of 19.15, this repository likely appeals to developers seeking more nuanced approaches to data protection.
kytmanov/obsidian-llm-wiki-local has attracted attention with 490 stars and a growth score of 16.78 for its implementation of Karpathy’s LLM Wiki using Ollama, allowing users to create a local wiki that auto-links and grows without sharing notes. This repository's popularity highlights the growing interest in creating more private and secure LLM-powered tools.