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Crush is a next-generation, terminal-based AI coding assistant developed by Charm, designed to seamlessly integrate with your tools, workflows, and preferred LLMs. It provides developers with an intuitive, session-based experience where multiple contexts can be managed across projects. With flexible model switching, Crush allows you to change providers mid-session while retaining conversation history.

Vibekit is an open-source toolkit focused on rapid prototyping and building of AI-driven experiences, particularly those that integrate multimodal inputs, reactive interfaces, and context-aware behaviors. It provides a set of abstractions and utilities that let developers connect generative models to UI frameworks, sensors, event streams, and external services without having to build plumbing from scratch. Instead of treating AI models as black boxes behind simple prompts, Vibekit encourages...

MiniMax-M2 is an open-weight large language model designed specifically for high-end coding and agentic workflows while staying compact and efficient. It uses a Mixture-of-Experts (MoE) architecture with 230 billion total parameters but only 10 billion activated per token, giving it the behavior of a very large model at a fraction of the runtime cost. The model is tuned for end-to-end developer flows such as multi-file edits, compile–run–fix loops, and test-validated repairs across real...

Groq AppGen is an interactive web application (built with Next.js and TypeScript) that uses Groq’s LLM API to generate or modify web application code based on natural-language prompts. Essentially, you tell the app what kind of web app or page you want (in plain English), and groq-appgen will produce HTML/JSX code scaffolding, layout, and optionally application logic accordingly. It supports iterative feedback: you can refine your prompt, adjust parameters or requirements, and have the app...

Qwen2.5-Coder, developed by QwenLM, is an advanced open-source code generation model designed for developers seeking powerful and diverse coding capabilities. It includes multiple model sizes—ranging from 0.5B to 32B parameters—providing solutions for a wide array of coding needs. The model supports over 92 programming languages and offers exceptional performance in generating code, debugging, and mathematical problem-solving. Qwen2.5-Coder, with its long context length of 128K tokens, is...