stepfun · Open weights
Step 3.5 Flash
StepFun's most capable open-source reasoning model with visible reasoning traces. Built on a sparse Mixture-of-Experts architecture with 196B total parameters and only 11B active per token, it achieves frontier-level performance in math, logic, and agentic coding while reaching up to 350 tokens/sec. Supports 256K context. NOTE: This model runs via StepFun, which may log and train on your prompts.
- Reasoning
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.10
- Output
- $0.30
Reference prices as published by the model provider. API example
Specifications
- Context window
- 262.1K
- Max output
- 65.5K
- Average output (7 days)
- 2.4K tokens
- Longer than 94% of 468 models
Side by side
Step 3.5 Flash compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Step 3.5 FlashstepfunThis model | Step 3.7 Flash ThinkingstepfunRemove | |
|---|---|---|
| Provider | stepfun | stepfun |
| Discovery tier | Open weights | Open weights |
| Added | Feb 2, 2026 | May 29, 2026 |
| Limits | ||
| Context window | 262.14K | 262.14K |
| Max output | 65.54K | 256KBest |
| Average output | 2.4K tokens | 7.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10Best | $0.20 |
| Output | $0.30Best | $1.15 |
| Cache read | — | $0.04 |
| Performance | ||
| Request success (24h) | 100.0% | 100.0% |
| Benchmark indexes | ||
| Intelligence Index | 16.6 | — |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | No | Yes |
| Vision | No | Yes |
| Structured output | No | Yes |
| Video input | No | Yes |
| Reasoning effort | — | none, low, medium, high |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Step 3.5 Flash
- Step 3.7 Flash Thinking
Intelligence Index
- Step 3.5 Flash16.6
- Step 3.7 Flash Thinking—
Step 3.5 Flash: Better than 43% of 326 scored models
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Step 3.5 Flash: 50.0%
- Step 3.7 Flash Thinking: —
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Step 3.5 Flash: 21.1%
- Step 3.7 Flash Thinking: —
GPQA Diamond
Graduate-level science questions
- Step 3.5 Flash: 83.1%
- Step 3.7 Flash Thinking: —
IFBench
Following precise output instructions
- Step 3.5 Flash: 64.6%
- Step 3.7 Flash Thinking: —
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Step 3.5 Flash: 27.3%
- Step 3.7 Flash Thinking: —
τ²-Bench Telecom
Tool use in a customer-support simulation
- Step 3.5 Flash: 94.4%
- Step 3.7 Flash Thinking: —
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Step 3.5 Flash: 50.0%
- Step 3.7 Flash Thinking: —
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
- 0.0%
- 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-ai/step-3.5-flash",
"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-ai/step-3.5-flash",
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.