stepfun · Balanced
Step 5 Preview
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
Side by side
Step 5 Preview compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Step 5 PreviewstepfunThis model | Step 3.5 FlashstepfunRemove | |
|---|---|---|
| Provider | stepfun | stepfun |
| Discovery tier | Balanced | Open weights |
| Added | Sep 20, 2026 | Feb 2, 2026 |
| Limits | ||
| Context window | 1MBest | 262.14K |
| Max output | 65.54K | 65.54K |
| Average output | 1.5K tokens | 2.4K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $1.00 | $0.10Best |
| Output | $2.70 | $0.30Best |
| Cache read | $0.05 | — |
| Performance | ||
| Request success (24h) | 100.0% | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | 43.7Best | 16.6 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | No |
| Vision | Yes | No |
| Structured output | Yes | No |
| Video input | Yes | No |
| Parallel tools | Yes | No |
| Reasoning effort | low, medium, high | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Step 5 Preview
- Step 3.5 Flash
Intelligence Index
- Step 5 Preview43.7
- Step 3.5 Flash16.6
Step 5 Preview: Better than 89% of 326 scored models
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- Step 5 Preview: 51.0%
- Step 3.5 Flash: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Step 5 Preview: 17.7%
- Step 3.5 Flash: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Step 5 Preview: 1,423 Elo
- Step 3.5 Flash: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Step 5 Preview: 1,587 Elo
- Step 3.5 Flash: —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Step 5 Preview: 14.8%
- Step 3.5 Flash: —
AA-LCRv1.1
Reasoning across long documents
- Step 5 Preview: 88.3%Top
- Step 3.5 Flash: 50.0%
MLCR-AA
Long-context reasoning over medical records
- Step 5 Preview: 18.3%
- Step 3.5 Flash: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Step 5 Preview: 46.5%Top
- Step 3.5 Flash: 21.1%
GPQA Diamond
Graduate-level science questions
- Step 5 Preview: —
- Step 3.5 Flash: 83.1%
IFBench
Following precise output instructions
- Step 5 Preview: —
- Step 3.5 Flash: 64.6%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Step 5 Preview: 33.3%
- Step 3.5 Flash: —
SciCode
Scientific computing in Python
- Step 5 Preview: 58.9%
- Step 3.5 Flash: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Step 5 Preview: —
- Step 3.5 Flash: 27.3%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Step 5 Preview: —
- Step 3.5 Flash: 94.4%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Step 5 Preview: 88.3%Top
- Step 3.5 Flash: 50.0%
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.
- 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.
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
Related models
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