Download
IQuest-Coder-V1 is a cutting-edge family of open-source large language models specifically engineered for code generation, deep code understanding, and autonomous software engineering tasks. These models range from tens of billions to smaller footprints and are trained on a novel code-flow multi-stage paradigm that captures how real software evolves over time — not just static code snapshots — giving them a deeper semantic understanding of programming logic. They support native long contexts up to 128K tokens, enabling them to reason across large codebases and multi-file interactions without context fragmentation, and include “Thinking” variants optimized for complex reasoning and “Loop” variants with recurrent mechanisms to improve inference efficiency. IQuest-Coder-V1 delivers state-of-the-art performance on multiple coding benchmarks, demonstrating strong results in competitive programming, tool use, and agentic code generation.
Features
- Code-flow multi-stage training paradigm
- Models from 7B to 40B parameters with “Thinking” and “Loop” variants
- Native support for ultra-long 128K token contexts
- Strong benchmark performance on SWE-Bench and LiveCodeBench
- Easy integration with Transformers and vLLM deployment
- Efficient inference with grouped query attention
Project Samples
