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stepfun · Balanced

Step 5 Preview

Added Sep 20, 2026

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Use in the app

Step 5 Preview is StepFun's 600B sparse MoE frontier model for production-scale agents, activating 27B parameters per token. It is built for software engineering, long-horizon tool use, research, professional knowledge work, and finance, with native text, image, and video understanding and a 1M-token context window. ⚠️ Note: This model routes through StepFun, so privacy and logging guarantees may be limited.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Video input
  • Parallel tools
Input
Text, Images, Video
Output
Text
Reasoning effort
low · medium · high
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$1.00
Output
$2.70
Cache read
$0.05

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K
Average output (7 days)
1.5K tokens
Longer than 86% of 465 models

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TryKimi K3 TEEClaude Haiku 5.5Grok 4.6All 3

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

Intelligence Index

43.7

Better than 89% of 326 scored models

3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    51.0%

    Workflow automation, penalized for guardrail violations

    Better than 65% of 173 scored models

  • AutomationBench-AA tasks completed

    17.7%

    Workflows finished end to end without a guardrail violation

    Better than 64% of 173 scored models

  • AA-Briefcasev1.1

    1,423 Elo

    Agentic knowledge work, rated head to head

    Better than 76% of 166 scored models

  • GDPval-AAv2.1

    1,587 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 82% of 187 scored models

Document reasoning

  • GDP.pdf

    14.8%

    Professional reasoning over PDF documents, all-pass rate

    Better than 64% of 171 scored models

  • AA-LCRv1.1

    88.3%

    Reasoning across long documents

    Better than 99% of 309 scored models

  • MLCR-AA

    18.3%

    Long-context reasoning over medical records

    Better than 73% of 121 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    46.5%

    Expert-level questions across academic fields

    Better than 89% of 323 scored models

Coding

  • Terminal-Benchv4.0

    33.3%

    Practical software engineering in a terminal

    Better than 80% of 171 scored models

  • SciCode

    58.9%

    Scientific computing in Python

    Better than 89% of 174 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    88.3%

    Long-context reasoning, earlier grading

    Better than 99% of 309 scored models

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
32.5%
About $0.69 per 1M input tokens with caching
Request success (24h)
100.0%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 100.0%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "stepfun/step-5-preview",
    "reasoning_effort": "medium",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="stepfun/step-5-preview",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

stepfun

Other stepfun models, starting with the same family.