Today's AI Frameworks & SDKs: Fastest-Growing Projects — May 07, 2026
Today's AI Frameworks & SDKs, we see a surge of interest in tools that enable developers to build and deploy large language models (LLMs) on various platforms. The trend is driven by the growing demand for AI-powered applications, and developers are looking for efficient ways to integrate LLMs into their projects. As a result, repositories focused on LLM deployment, management, and optimization have seen significant growth.
warpdot-dev/craft-agents-oss, with a growth score of 86.00 and 231 stars, is an open-source SDK for building desktop AI applications using Electron and Claude Agent. Its popularity stems from its ease of use and the ability to deploy LLMs on multiple platforms, making it an attractive choice for developers who want to create AI-powered desktop applications.
1bananachicken/MaaNTE, boasting a growth score of 80.68 and 908 stars, is a tool driven by the MAA Framework that provides a QQ exchange group for developers. Its high growth rate can be attributed to its popularity in the Chinese developer community, where it serves as a valuable resource for building and integrating AI models.
HKUDS-AI/polymarket-ai-trading, with a growth score of 79.35 and 138 stars, offers an AI-assisted paper trading framework for Polymarket using OpenAI insights and vector search. Its growth is driven by the increasing interest in AI-powered trading solutions, making it an attractive choice for developers looking to build automated trading systems.
noonghunna/club-3090, featuring a growth score of 73.28 and 611 stars, provides community recipes for serving LLMs on RTX 3090 GPUs. Its popularity stems from the growing demand for efficient LLM deployment on high-performance hardware, making it a go-to resource for developers who want to optimize their AI models.
alash3al/stash, with a growth score of 51.19 and 662 stars, offers a persistent memory layer for AI agents using Postgres. Its growth is driven by the need for efficient data management in AI applications, making it an attractive choice for developers looking to build scalable AI solutions.
TheTom/vllm-swift, boasting a growth score of 32.00 and 248 stars, provides a Metal plugin powered by mlx-swift for high-performance LLM inference on Apple Silicon. Its growth is driven by the increasing interest in deploying AI models on mobile devices, making it an attractive choice for developers who want to build AI-powered iOS applications.
jegly/Box, featuring a growth score of 22.82 and 313 stars, offers a private on-device AI suite for Android with support for llama.cpp and stable-diffusion.cpp. Its popularity stems from the growing demand for efficient on-device AI solutions, making it an attractive choice for developers who want to build AI-powered Android applications.
baidu-baige/LoongForge, with a growth score of 19.29 and 153 stars, provides a modular training framework for language, multimodal, and embodied models. Its growth is driven by the increasing interest in building complex AI models, making it an attractive choice for researchers and developers who want to train large-scale AI models.
Overall, Today's trends in AI Frameworks & SDKs highlight the growing demand for efficient LLM deployment, management, and optimization solutions across various platforms.
warpdot-dev/craft-agents-oss, with a growth score of 86.00 and 231 stars, is an open-source SDK for building desktop AI applications using Electron and Claude Agent. Its popularity stems from its ease of use and the ability to deploy LLMs on multiple platforms, making it an attractive choice for developers who want to create AI-powered desktop applications.
1bananachicken/MaaNTE, boasting a growth score of 80.68 and 908 stars, is a tool driven by the MAA Framework that provides a QQ exchange group for developers. Its high growth rate can be attributed to its popularity in the Chinese developer community, where it serves as a valuable resource for building and integrating AI models.
HKUDS-AI/polymarket-ai-trading, with a growth score of 79.35 and 138 stars, offers an AI-assisted paper trading framework for Polymarket using OpenAI insights and vector search. Its growth is driven by the increasing interest in AI-powered trading solutions, making it an attractive choice for developers looking to build automated trading systems.
noonghunna/club-3090, featuring a growth score of 73.28 and 611 stars, provides community recipes for serving LLMs on RTX 3090 GPUs. Its popularity stems from the growing demand for efficient LLM deployment on high-performance hardware, making it a go-to resource for developers who want to optimize their AI models.
alash3al/stash, with a growth score of 51.19 and 662 stars, offers a persistent memory layer for AI agents using Postgres. Its growth is driven by the need for efficient data management in AI applications, making it an attractive choice for developers looking to build scalable AI solutions.
TheTom/vllm-swift, boasting a growth score of 32.00 and 248 stars, provides a Metal plugin powered by mlx-swift for high-performance LLM inference on Apple Silicon. Its growth is driven by the increasing interest in deploying AI models on mobile devices, making it an attractive choice for developers who want to build AI-powered iOS applications.
jegly/Box, featuring a growth score of 22.82 and 313 stars, offers a private on-device AI suite for Android with support for llama.cpp and stable-diffusion.cpp. Its popularity stems from the growing demand for efficient on-device AI solutions, making it an attractive choice for developers who want to build AI-powered Android applications.
baidu-baige/LoongForge, with a growth score of 19.29 and 153 stars, provides a modular training framework for language, multimodal, and embodied models. Its growth is driven by the increasing interest in building complex AI models, making it an attractive choice for researchers and developers who want to train large-scale AI models.
Overall, Today's trends in AI Frameworks & SDKs highlight the growing demand for efficient LLM deployment, management, and optimization solutions across various platforms.