Скачать или смотреть Step 3.5 Flash Technical Report

Step 3.5 Flash is a high-performance open-source foundation model designed by StepFun to bridge the gap between rapid inference and deep reasoning capabilities. Utilizing a sparse Mixture of Experts (MoE) architecture, the model selectively activates only 11 billion of its total 196 billion parameters during generation, enabling it to achieve exceptional processing speeds of up to 350 tokens per second while maintaining the intelligence density required for complex tasks. This efficiency allows for secure local deployment on high-end consumer hardware and supports a cost-effective 256K context window through a hybrid Sliding Window Attention mechanism. The model is specifically engineered for agentic applications, leveraging a novel reinforcement learning framework called Metropolis Independence Sampling Filtered Policy Optimization (MIS-PO) to ensure stability and continuous self-improvement in long-horizon workflows like coding, deep research, and multi-step problem solving. By combining these architectural innovations with strong performance on mathematics and coding benchmarks, Step 3.5 Flash functions not merely as a chatbot, but as a reliable agent capable of orchestrating tools and executing autonomous actions with professional-grade precision.

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