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 Flash 2603stepfunRemove | |
|---|---|---|
| Provider | stepfun | stepfun |
| Discovery tier | Balanced | Open weights |
| Added | Sep 20, 2026 | Apr 14, 2026 |
| Limits | ||
| Context window | 1MBest | 262.14K |
| Max output | 65.54K | 65.54K |
| Average output | 1.5K tokens | 3K 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 | 17.0 |
| 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 2603
Intelligence Index
- Step 5 Preview43.7
- Step 3.5 Flash 260317.0
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 2603: —
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- Step 5 Preview: 17.7%
- Step 3.5 Flash 2603: —
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- Step 5 Preview: 1,423 Elo
- Step 3.5 Flash 2603: —
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- Step 5 Preview: 1,587 Elo
- Step 3.5 Flash 2603: —
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- Step 5 Preview: 14.8%
- Step 3.5 Flash 2603: —
AA-LCRv1.1
Reasoning across long documents
- Step 5 Preview: 88.3%Top
- Step 3.5 Flash 2603: 63.0%
MLCR-AA
Long-context reasoning over medical records
- Step 5 Preview: 18.3%
- Step 3.5 Flash 2603: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Step 5 Preview: 46.5%Top
- Step 3.5 Flash 2603: 24.5%
GPQA Diamond
Graduate-level science questions
- Step 5 Preview: —
- Step 3.5 Flash 2603: 82.6%
IFBench
Following precise output instructions
- Step 5 Preview: —
- Step 3.5 Flash 2603: 66.5%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- Step 5 Preview: 33.3%
- Step 3.5 Flash 2603: —
SciCode
Scientific computing in Python
- Step 5 Preview: 58.9%
- Step 3.5 Flash 2603: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Step 5 Preview: —
- Step 3.5 Flash 2603: 32.6%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Step 5 Preview: —
- Step 3.5 Flash 2603: 87.4%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Step 5 Preview: 88.3%Top
- Step 3.5 Flash 2603: 63.0%
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
Other stepfun models, starting with the same family.