IQuest Coder State-of-the-art open-source code LLM for autonomous software engineering. Built with the innovative Code-Flow training paradigm to understand real-world code evolution. Explore Models Technical Report GitHub 76.2% SWE-Bench Verified View Results 81.1% LiveCodeBench v6 View Results 49.9% BigCodeBench View Results 128K Context Length Learn More Built for Code Intelligence Advancing autonomous software engineering with innovative training paradigms and efficient architectures. 🔄 Code-Flow Training Moving beyond static code representations, our models learn from repository evolution patterns, commit transitions, and dynamic code transformations to understand real-world software development processes. 🧠 Dual Specialization Bifurcated post-training delivers two specialized variants: Thinking models with reasoning-driven RL for complex problem-solving, and Instruct models optimized for general coding assistance. ♾ Loop Architecture The Loop variant introduces a recurrent mechanism with shared parameters across iterations, optimizing the trade-off between model capacity and deployment footprint. 📄 Native Long Context All models natively support up to 128K tokens without requiring additional scaling techniques, enabling processing of entire codebases and multi-file contexts.

IQuest Coder

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iquestcoder