StepFun, released Jan 29, 2026

Step 3.5 Flashprice, context, benchmarks and release details

Provisional: not enough results to rank yet Open weights 88% confidence 88 percent, High confidence, 2 of 3 expected sources in
53.0
SI Score
#98 of 142 ranked models
Input, per 1M tokens
$0.10models.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-3.5-flash Retrieved Oct 9, 2026 · MIT
Open source ↗
Output, per 1M tokens
$0.30models.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-3.5-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
Jan 29, 2026models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

How the score breaks down

Coding (weight 40 percent) 50.9
Math (weight 15 percent) —
Preference (weight 15 percent) 73.4
Reasoning (weight 30 percent) —

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, 05:13 UTC.

Around it on the leaderboard

  1. 96 DeepSeek V3.2 53.3
  2. 97 GLM-4.7-Flash 53.3
  3. 98 Step 3.5 Flash 53.0
  4. 99 Qwen3 30B A3B 52.6
  5. 100 GPT OSS 20B 52.5

Full leaderboard

Benchmark results

3 benchmarks, 3 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.

SWE-bench Verifiedcoding 74.4%Official model cards via models.devLab-reported; metric resolved; transcribed by MIT models.dev catalog; not independently evaluated [variant] Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
74.4
Terminal-Benchcoding 27.3%Official model cards via models.devLab-reported; metric success rate; transcribed by MIT models.dev catalog; not independently evaluated [variant] Published Jun 2, 2026 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
27.3
LMArena Textpreference 1402.9 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗
73.4

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
textmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
70% of expected source weight

Reported (2)

  • Official model cards via models.devOct 8, 2026
  • LMArena / ArenaOct 8, 2026

Awaiting (1)

  • LiveBench30% 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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