「北京版幻方」冷不丁开源SOTA代码大模型！一张3090就能跑，40B参数掀翻Opus-4.5和GPT-5.2

Core Insights - The article highlights the emergence of the IQuest-Coder-V1 model series, which has gained significant attention in the tech community for its performance in code generation and understanding tasks [1][2]. Model Performance - The IQuest-Coder-V1 model, particularly the 40B parameter version, achieved an impressive score of 81.4% on the SWE-Bench Verified leaderboard, surpassing models like Claude Opus-4.5 and GPT-5.2, which are speculated to have parameter scales in the hundreds of billions to trillions [2][50]. - The model series includes versions with 7B, 14B, and 40B parameters, each offering Instruct and Thinking variants tailored for different use cases [14][15]. Technical Specifications - The IQuest-Coder-V1 series emphasizes "engineering-friendly" design and long context usability, supporting a maximum context length of 128K tokens and a vocabulary size of 76,800 tokens [22][25]. - The 40B parameter version features a Loop variant that enhances parameter utilization efficiency, achieving significant reductions in HBM and KV Cache overhead while improving throughput [19][20]. Training Methodology - The training strategy, termed "code-flow multi-stage training," focuses on learning from the evolution of code rather than static code snippets, incorporating a triplet data structure to capture changes over a project's lifecycle [38][43]. - This approach allows the model to understand the dynamic evolution of software logic, capturing differences before and after modifications [46][47]. Deployment and Accessibility - The models are designed for deployment on consumer-grade GPUs, with the Int4 version capable of running on a single H20 inference card [53][54]. - The IQuest-Coder series has been open-sourced on platforms like GitHub, making it accessible for developers and researchers [11]. Company Background - IQuest-Coder is developed by Ubiquant Holding Limited (九坤投资), a prominent quantitative investment firm in China, known for its focus on AI and high-frequency trading [57][64]. - The company has established multiple research labs, including an AI Lab, and has a strong team with a high percentage of members holding advanced degrees from top universities [62][64].