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IQuest Research Open-Sources 320B Agentic Coding Model
Original: IQuest Research Open-Sources IQuest-Q1, a 320B MoE Model for Agentic Coding With 15B Active Parameters
AI startup IQuest Research has released IQuest-Q1, an open-source mixture-of-experts model with 320 billion total parameters but only 15 billion active per query, aimed at agentic coding tasks. The sparse architecture promises large-model capability with much lower inference costs. It arrives as competition intensifies among open-weight coding models, and developers are weighing its benchmarks and licensing against rivals like DeepSeek and Qwen.
Why now: New open-source releases of large coding models draw immediate attention from developers evaluating cost-efficient alternatives to closed AI systems.
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