iQuest-Coder is here! A brand-new open-source coding model from Quest Research, backed by China’s quant giant UBIQUANT, claiming to rival Claude Sonnet 4.5 and Gemini 3.0! In this video, we break down the 40B Loop variants, their Loop architecture, Code-Flow training, and the crazy 128K token support. We also dive into benchmarks vs reality, community skepticism, and real-world coding tests.
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📌 LINKS & RESOURCES
Blog: https://iquestlab.github.io/
Github: https://github.com/IQuestLab/IQuest-Coder-V1
Demo Videos: https://x.com/HaohaoHenr56041
HuggingFace Model Card: https://huggingface.co/IQuestLab
Is iQuest-Coder really the next-gen DeepSeek 2.0, or just hype? Find out now! ⚡💻
Features Highlighted:
Loop architecture with recurrent mechanism ♻️
128K native token support 📜
Dual post-training paths: Thinking & Instruct 🧠
Efficient deployment on single GPUs 🚀
Competitive programming & software engineering focus 🖥️
Hashtags:
#iQuestCoder #OpenSourceAI #CodingLLM #AIProgramming #Claude4 #GPT5 #DeepSeek2 #SoftwareEngineering #CompetitiveProgramming #NextGenAI #AIModels #MachineLearning #LoopArchitecture
Tags (split by commas):
iQuest Coder, open source AI, coding LLM, Claude Sonnet 4.5, Gemini 3.0, DeepSeek 2.0, AI coding assistant, AI for developers, Loop architecture, Code-Flow training, software engineering AI, competitive programming AI, 128k token LLM, single GPU deployment, AI benchmarks, next-gen AI, AI coding model, agentic coding, AI programming tools
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