stepfun · Open weights
Step 3.5 Flash 2603
Step 3.5 Flash 2603 is optimized for high-frequency agentic and coding workflows with improved token efficiency and faster reasoning. 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)
- 3K tokens
- Longer than 96% of 465 models
Side by side
Step 3.5 Flash 2603 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| Step 3.5 Flash 2603stepfunThis model | GLM 4.7Z.aiRemove | |
|---|---|---|
| Provider | stepfun | Z.ai |
| Discovery tier | Open weights | Open weights |
| Added | Apr 14, 2026 | Dec 22, 2025 |
| Limits | ||
| Context window | 262.14KBest | 200K |
| Max output | 65.54KBest | 65.54K |
| Average output | 3K tokens | 539 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.10Best | $0.40 |
| Output | $0.30Best | $1.93 |
| Cache read | — | $0.0801 |
| Performance | ||
| Throughput | — | 74.0 tok/s |
| Time to first token | — | 2.4 s |
| Request success (24h) | 100.0%Best | 99.8% |
| Benchmark indexes | ||
| Intelligence Index | 17.0 | 17.4Best |
| Math Index | — | 48.0 |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | No | Yes |
| Structured output | No | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- Step 3.5 Flash 2603
- GLM 4.7
Intelligence Index
- Step 3.5 Flash 260317.0
- GLM 4.717.4
Step 3.5 Flash 2603: Better than 45% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- Step 3.5 Flash 2603: —
- GLM 4.7: 48.0
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- Step 3.5 Flash 2603: 63.0%Top
- GLM 4.7: 40.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- Step 3.5 Flash 2603: 24.5%Top
- GLM 4.7: 6.4%
GPQA Diamond
Graduate-level science questions
- Step 3.5 Flash 2603: 82.6%Top
- GLM 4.7: 66.4%
MMLU-Pro
Multi-subject knowledge and reasoning
- Step 3.5 Flash 2603: —
- GLM 4.7: 79.4%
IFBench
Following precise output instructions
- Step 3.5 Flash 2603: 66.5%Top
- GLM 4.7: 54.6%
Coding
LiveCodeBench
Recent competitive programming problems
- Step 3.5 Flash 2603: —
- GLM 4.7: 56.2%
Math
AIME 2025
Competition mathematics, 2025 problems
- Step 3.5 Flash 2603: —
- GLM 4.7: 48.0%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- Step 3.5 Flash 2603: 32.6%Top
- GLM 4.7: 30.3%
τ²-Bench Telecom
Tool use in a customer-support simulation
- Step 3.5 Flash 2603: 87.4%
- GLM 4.7: 94.2%Top
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- Step 3.5 Flash 2603: 63.0%Top
- GLM 4.7: 40.7%
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-2603",
"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-2603",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)stepfun
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