StepFun Launches Step 5 Preview: 600B-Total, 27B-Active MoE Model With 1M-Token Context

StepFun has released a preview of Step 5, a Mixture-of-Experts model with 600 billion total parameters and 27 billion active parameters per forward pass, specifically designed for long-horizon agentic tasks with a one-million-token context window. The MoE architecture means developers get frontier-scale capability at a fraction of the inference cost of a dense 600B model, since only 27B parameters activate per token. The 1M context window is a critical feature for agentic workflows that require maintaining long conversation histories, processing large codebases, or handling extended document analysis in a single pass. StepFun is positioning Step 5 as a direct competitor to models like Gemini 1.5 Pro in the long-context agentic space, which is currently one of the most contested capability frontiers. Developers building autonomous agents or RAG-free long-document pipelines should watch this closely and evaluate the preview API if available.