Model Library/Step 3.7 Flash
Step 3.7 Flash

Step 3.7 Flash

stepfun/step-3.7-flash
by StepFun
Input price
$0.2/ M tokens
Output price
$1.15/ M tokens
Context window
256Ktokens
Max output
250Ktokens

Step-3.7-Flash is StepFun's flagship high-efficiency multimodal reasoning model, built on a sparse Mixture-of-Experts architecture (198B total / ~11B active parameters) that delivers high throughput and low latency for real-time agentic workflows and high-frequency calls. It natively understands images and video — no extra vision model needed in agent frameworks — and offers a 256K context window with three selectable reasoning levels (low/medium/high) to balance speed, cost and reasoning depth. With reliable multi-step tool calling, task decomposition and plan execution, it excels at coding, solution planning and vision-to-workflow tasks, producing complete plans in a single call.

Features

Serverless API

Docs

stepfun/step-3.7-flash is available via Novita's serverless API, where you pay per token. There are several ways to call the API, including OpenAI-compatible endpoints with exceptional reasoning performance.

Available Serverless

Run queries immediately, pay only for usage

Input$0.2 / M Tokens
Cache Read$0.04 / M Tokens
Output$1.15 / M Tokens
  1. Get your API key

    Sign up and create a key to run the code below. The API is OpenAI-compatible.

  2. Make your first request

    The API is OpenAI-compatible: point any OpenAI SDK at the base URL and pass this model ID.

    Base URL
    https://api.novita.ai/openai
    Model ID
    stepfun/step-3.7-flash
    API Endpoint
    chat/completions
    1from openai import OpenAI
    2
    3client = OpenAI(
    4    api_key="<Your API Key>",
    5    base_url="https://api.novita.ai/openai"
    6)
    7
    8response = client.chat.completions.create(
    9    model="stepfun/step-3.7-flash",
    10    messages=[
    11        {"role": "system", "content": "You are a helpful assistant."},
    12        {"role": "user", "content": "Hello, how are you?"}
    13    ],
    14    max_tokens=256000,
    15    temperature=0.7
    16)
    17
    18print(response.choices[0].message.content)