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stepfun · Open weights

Step 3.5 Flash

Added Feb 2, 2026Open weights

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Use in the app

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.

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Step 3.5 FlashstepfunThis modelGemma 4 26B A4BGoogleRemove
ProviderstepfunGoogle
Discovery tierOpen weightsOpen weights
AddedFeb 2, 2026Apr 2, 2026
Limits
Context window262.14K262.14K
Max output65.54K131.07KBest
Average output2.4K tokens131 tokens
Pricing, USD per 1M tokens
Input$0.10$0.09Best
Output$0.30$0.30
Cache read—$0.05
Performance
Throughput—62.5 tok/s
Time to first token—2.2 s
Request success (24h)100.0%100.0%
Benchmark indexes
Intelligence Index16.616.7Best
Coding Index—39.3
Capabilities
ReasoningYesYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
Video inputNoYes
Reasoning effort——

Public evaluations

Benchmarks

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

  • Step 3.5 Flash
  • Gemma 4 26B A4B

Intelligence Index

  • Step 3.5 Flash16.6
  • Gemma 4 26B A4B16.7

Step 3.5 Flash: Better than 43% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • Step 3.5 Flash: —
    • Gemma 4 26B A4B: 39.3

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • Step 3.5 Flash: —
    • Gemma 4 26B A4B: 1.9%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • Step 3.5 Flash: —
    • Gemma 4 26B A4B: 0.2%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • Step 3.5 Flash: —
    • Gemma 4 26B A4B: 315 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • Step 3.5 Flash: —
    • Gemma 4 26B A4B: 565 Elo

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • Step 3.5 Flash: 50.0%
    • Gemma 4 26B A4B: 65.7%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • Step 3.5 Flash: 21.1%Top
    • Gemma 4 26B A4B: 19.3%

  • GPQA Diamond

    Graduate-level science questions

    • Step 3.5 Flash: 83.1%Top
    • Gemma 4 26B A4B: 79.2%

  • IFBench

    Following precise output instructions

    • Step 3.5 Flash: 64.6%
    • Gemma 4 26B A4B: 72.4%Top

Coding

  • SciCode

    Scientific computing in Python

    • Step 3.5 Flash: —
    • Gemma 4 26B A4B: 40.0%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • Step 3.5 Flash: 27.3%Top
    • Gemma 4 26B A4B: 13.6%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • Step 3.5 Flash: 94.4%Top
    • Gemma 4 26B A4B: 43.6%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • Step 3.5 Flash: 50.0%
    • Gemma 4 26B A4B: 65.7%Top

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.

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-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

Other stepfun models, starting with the same family.