StepFun, released May 29, 2026

Step 3.7 Flashprice, context, benchmarks and release details

Provisional: not enough results to rank yet Open weights 13% confidence 13 percent, Low confidence, 1 of 3 expected sources in
50.3
SI Score
Not ranked yet
Input, per 1M tokens
$0.18models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.stepfun.com/docs/zh/overview/concept. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; stepfun/step-3.7-flash Retrieved Oct 9, 2026 · MIT
Open source ↗
Output, per 1M tokens
$1.11models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.stepfun.com/docs/zh/overview/concept. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; stepfun/step-3.7-flash Retrieved Oct 9, 2026 · MIT
Open source ↗
Context window
256Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
256Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
May 29, 2026models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

How the score breaks down

Coding (weight 40 percent) 57.0
Math (weight 15 percent) —
Preference (weight 15 percent) —
Reasoning (weight 30 percent) 47.2

Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 06:15 UTC.

Around it on the leaderboard

  1. 1 Claude Fable 5.1 80.2
  2. 2 Claude Opus 5.5 78.4
  3. 3 GPT-6 Astra 77.5
  4. 4 Claude Fable 5 76.8
  5. 5 Claude Opus 5 74.9

Full leaderboard

Benchmark results

5 benchmarks, 5 results

Each row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.

Humanity's Last Exam (with tools)reasoning 47.2%Official model cards via models.devLab-reported; metric accuracy; transcribed by MIT models.dev catalog; not independently evaluated [variant] with toolsPublished May 29, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
47.2
SWE-bench Procoding 56.3%Official model cards via models.devLab-reported; metric resolve rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published May 29, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
56.3
SWE-bench Verifiedcoding 76.5%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published May 29, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
76.5
Terminal-Benchcoding 35.6%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published Jun 15, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
35.6
Terminal-Bench 2.1coding 59.6%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] 2.1Published May 29, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
59.6

Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.

Details and sources

Open weights
Yesmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
text, image, videomodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
10% of expected source weight

Reported (1)

  • Official model cards via models.devOct 8, 2026

Awaiting (2)

  • LiveBench30% of weight
  • LMArena / Arena60% of weight

Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.

What changed

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Alerts on this device

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