Today's AI Frameworks & SDKs: Fastest-Growing Projects — May 25, 2026
Today's AI Frameworks & SDKs space continues to show a strong focus on virtualization and inference acceleration, with several projects gaining significant traction among developers and researchers alike. This trend reflects an increasing demand for scalable and efficient solutions that can handle the computational demands of large language models (LLMs) and other advanced AI agents.
strukto-ai/mirage
Mirage is a unified virtual filesystem designed specifically for AI agents, enabling them to interact with data in a more intuitive and consistent manner. Its impressive growth score indicates its potential as an essential tool for managing complex AI environments, making it appealing to developers working on sophisticated AI applications that require robust file management capabilities.
lightseekorg/tokenspeed
TokenSpeed is described as a speed-of-light LLM inference engine, designed to enhance the performance of large language models. With 54.24 in growth score and over 1,000 stars, it demonstrates significant interest from developers looking for high-performance solutions that can accelerate model execution without compromising on accuracy or functionality.
simonlin1212/TradingAgents-astock
This project offers a multi-agent investment research framework tailored specifically to the A-share market in China. The growth score of 51.96 suggests it is attracting attention from financial analysts and investors interested in leveraging AI-driven strategies for stock analysis and decision-making within the unique context of the Chinese market.
deeplethe/forkd
Forkd provides a high-speed method to spawn and manage AI agent microVMs, allowing developers to quickly create isolated environments. Its growth score of 51.71 reflects its growing popularity among those seeking efficient ways to handle multiple virtual machine instances for testing or deployment purposes.
1bananachicken/MaaNTE
MaaNTE is a framework driven by MAAFramework and aimed at facilitating interaction with AI systems through an intuitive interface. With over 1,500 stars and a growth score of 43.40, it appears to be resonating well among developers who need streamlined tools for managing complex AI workflows.
noonghunna/club-3090
This repository offers community recipes for serving LLMs on NVIDIA RTX 3090 GPUs using multiple engines such as vLLM and llama.cpp. Its growth score of 34.72 suggests it is becoming an important resource for developers aiming to optimize their models' performance on specific hardware configurations.
jhaizhou-ops/pinrule
PinRule provides a universal framework for setting AI behavior rules, ensuring that AI systems adhere strictly to predefined guidelines during long-running tasks. Although its star count remains relatively low at 30, the high growth score of 26.38 indicates it is gaining traction among developers looking for robust rule-based management solutions in AI applications.
zimingttkx/QuantumFlow
QuantumFlow offers a distributed LLM inference scheduling framework with support for multiple backends and adaptive scheduling strategies. Its growth score of 24.89 suggests it is becoming an attractive option for those managing large-scale deployment of language models across different infrastructure setups.
Ontos-AI/knowhere
Knowhere extracts, parses, and outputs structured chunks of data ready for AI agents and retrieval-augmented generation (RAG) systems. With a growth score of 24.04, it appears to be gaining traction among developers who need tools that can efficiently process unstructured data into formats suitable for advanced AI applications.
OmYarewar/PHANTOM
PHANTOM is an AI-powered pentesting command center designed to automate security testing with real-time streaming capabilities and a self-improving AI system. Its growth score of 19.60 reflects its growing relevance among cybersecurity professionals who seek cutting-edge tools for automated penetration testing.
These projects collectively highlight the ongoing innovation in the development of scalable, efficient, and versatile frameworks that cater to the diverse needs of the AI community, from financial analysis to security testing and beyond.
strukto-ai/mirage
Mirage is a unified virtual filesystem designed specifically for AI agents, enabling them to interact with data in a more intuitive and consistent manner. Its impressive growth score indicates its potential as an essential tool for managing complex AI environments, making it appealing to developers working on sophisticated AI applications that require robust file management capabilities.
lightseekorg/tokenspeed
TokenSpeed is described as a speed-of-light LLM inference engine, designed to enhance the performance of large language models. With 54.24 in growth score and over 1,000 stars, it demonstrates significant interest from developers looking for high-performance solutions that can accelerate model execution without compromising on accuracy or functionality.
simonlin1212/TradingAgents-astock
This project offers a multi-agent investment research framework tailored specifically to the A-share market in China. The growth score of 51.96 suggests it is attracting attention from financial analysts and investors interested in leveraging AI-driven strategies for stock analysis and decision-making within the unique context of the Chinese market.
deeplethe/forkd
Forkd provides a high-speed method to spawn and manage AI agent microVMs, allowing developers to quickly create isolated environments. Its growth score of 51.71 reflects its growing popularity among those seeking efficient ways to handle multiple virtual machine instances for testing or deployment purposes.
1bananachicken/MaaNTE
MaaNTE is a framework driven by MAAFramework and aimed at facilitating interaction with AI systems through an intuitive interface. With over 1,500 stars and a growth score of 43.40, it appears to be resonating well among developers who need streamlined tools for managing complex AI workflows.
noonghunna/club-3090
This repository offers community recipes for serving LLMs on NVIDIA RTX 3090 GPUs using multiple engines such as vLLM and llama.cpp. Its growth score of 34.72 suggests it is becoming an important resource for developers aiming to optimize their models' performance on specific hardware configurations.
jhaizhou-ops/pinrule
PinRule provides a universal framework for setting AI behavior rules, ensuring that AI systems adhere strictly to predefined guidelines during long-running tasks. Although its star count remains relatively low at 30, the high growth score of 26.38 indicates it is gaining traction among developers looking for robust rule-based management solutions in AI applications.
zimingttkx/QuantumFlow
QuantumFlow offers a distributed LLM inference scheduling framework with support for multiple backends and adaptive scheduling strategies. Its growth score of 24.89 suggests it is becoming an attractive option for those managing large-scale deployment of language models across different infrastructure setups.
Ontos-AI/knowhere
Knowhere extracts, parses, and outputs structured chunks of data ready for AI agents and retrieval-augmented generation (RAG) systems. With a growth score of 24.04, it appears to be gaining traction among developers who need tools that can efficiently process unstructured data into formats suitable for advanced AI applications.
OmYarewar/PHANTOM
PHANTOM is an AI-powered pentesting command center designed to automate security testing with real-time streaming capabilities and a self-improving AI system. Its growth score of 19.60 reflects its growing relevance among cybersecurity professionals who seek cutting-edge tools for automated penetration testing.
These projects collectively highlight the ongoing innovation in the development of scalable, efficient, and versatile frameworks that cater to the diverse needs of the AI community, from financial analysis to security testing and beyond.