Skip to content
No models found
OpenRouter
© 2026 OpenRouter, Inc

Product

  • Chat
  • Rankings
  • Apps
  • Models
  • Providers
  • Pricing
  • Enterprise
  • Labs

Company

  • About
  • Announcements
  • CareersHiring
  • Privacy
  • Terms of Service
  • Support
  • State of AI
  • Works With OR
  • Data

Developer

  • Documentation
  • API Reference
  • SDK
  • Status

Connect

  • Discord
  • GitHub
  • LinkedIn
  • X
  • YouTube
Favicon for stepfun

StepFun: Step 3.7 Flash

stepfun/step-3.7-flash

Compare

Step 3.7 Flash is StepFun's latest high-efficiency multimodal Mixture-of-Experts model. It pairs a 196B-parameter language backbone with a vision encoder for native image and video understanding, activating roughly 11B parameters per token. The model supports a 256K context window and exposes selectable reasoning levels (high/medium/low), letting callers trade off speed, cost, and depth of reasoning.

Designed for coding, agentic workflows, structured outputs, and long-context productivity tasks.

Modalities

Input Price

$0.20per 1M

Output Price

$1.15per 1M

Context

256K

Weekly Tokens

1.16B

Released

May 28, 2026

Overview
Providers
Performance
Pricing
Apps
Activity
Uptime
API

Sample code and API for Step 3.7 Flash

OpenRouter normalizes requests and responses across providers for you.

1

Get your API key

Create an API key from your OpenRouter dashboard and set it as an environment variable:

2

Make your first request

Use stepfun/step-3.7-flash with the OpenRouter API:

OpenRouter supports reasoning-enabled models that can show their step-by-step thinking process. Use the reasoning parameter in your request to enable reasoning, and access the reasoning_details array in the response to see the model's internal reasoning before the final answer. When continuing a conversation, preserve the complete reasoning_details when passing messages back to the model so it can continue reasoning from where it left off. Learn more about reasoning tokens.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

3

Enable streaming

Add "stream": true to your request body to receive responses as server-sent events:

Endpoint

Sends a request for a model response for the given chat conversation. Supports both streaming and non-streaming modes.

POSThttps://openrouter.ai/api/v1/chat/completions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelstepfun/step-3.7-flash

Creates a streaming or non-streaming response using the OpenAI Responses API format.

Docs
POSThttps://openrouter.ai/api/v1/responses
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelstepfun/step-3.7-flash

Creates a message using the Anthropic Messages API format. Supports text, images, PDFs, tools, and extended thinking.

Docs
POSThttps://openrouter.ai/api/v1/messages
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelstepfun/step-3.7-flash

Parameters

NameTypeDefaultDescription
reasoningmap—Controls reasoning behavior for models that support thinking tokens, including whether reasoning is enabled, the reasoning effort, maximum reasoning tokens, and whether reasoning is excluded from the response.
temperaturefloat1This setting influences the variety in the model's responses.
max_tokensinteger—This sets the upper limit for the number of tokens the model can generate in response.
toolsarray—Tool calling parameter, following OpenAI's tool calling request shape.
top_pfloat1This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
stoparray—Stop generation immediately if the model encounter any token specified in the stop array.
frequency_penaltyfloat0This setting aims to control the repetition of tokens based on how often they appear in the input.
logprobsboolean—Whether to return log probabilities of the output tokens or not.
top_logprobsinteger—An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability.
response_formatmap—Forces the model to produce specific output format.