StepFun Launches Step 3.7 Flash with Adjustable Reasoning Levels

StepFun has released Step 3.7 Flash, a 196B-parameter Mixture-of-Experts (MoE) model that activates roughly 11B parameters per token during inference. The model includes native image and video understanding capabilities through an integrated vision encoder.

Technical Specifications

Step 3.7 Flash supports a 256K token context window and is priced at $0.20 per 1M input tokens and $1.15 per 1M output tokens. The model was released on May 28, 2025, according to OpenRouter's listing.

The architecture combines a 196B-parameter language backbone with a vision encoder, making it StepFun's latest multimodal offering. By activating only 11B parameters per token through its MoE design, the model aims to balance performance with computational efficiency.

Selectable Reasoning Levels

A distinctive feature is the model's three selectable reasoning levels—high, medium, and low—allowing developers to trade off between processing speed, cost, and reasoning depth based on specific use cases. This gives callers direct control over how the model allocates compute resources per query.

Target Use Cases

According to StepFun, Step 3.7 Flash is designed for coding tasks, agentic workflows, structured output generation, and long-context productivity applications. The 256K context window positions it for document analysis, extended code review, and multi-turn conversations requiring substantial memory.

The model is currently available through OpenRouter, which routes requests across multiple providers to handle different prompt sizes and parameters.

What This Means

Step 3.7 Flash represents StepFun's entry into the competitive space of large-context multimodal models, directly competing with offerings from Anthropic, Google, and others in the 200K+ context range. The adjustable reasoning levels are a notable differentiation—most models offer fixed inference patterns, while this approach lets developers optimize for their specific latency and quality requirements. The $0.20/$1.15 pricing puts it in the mid-tier range, though real-world performance benchmarks will determine whether the selectable reasoning modes deliver meaningful value beyond standard inference optimization.