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Data

Data as of October 14, 2026 · How the score is built

CurrentOpen WeightReasoning

Released May 29, 2026256K context

Step 3.7 Flash

Decision readingStep 3.7 Flash scores 43.7 out of 100 and ranks #123 of 221. This profile shows 11 source-displayable benchmark rows; its strongest eligible category is Agentic at #73. API pricing is $0.2 input and $1.15 output per million tokens.

Released May 29, 2026 — see all recent releases

Decision snapshot

Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.

Capability

43.7/100

field median 50#123 of 221 ranked models

Public

#123of 221

Verified —

Price

$0.20input / $1.15 output

input median $0.78blended $0.67

Speed

185tok/s

field median 86 tok/sFirst token 13.36 s

Context

256Ktokens

field median 256,000Reported for this model; direct source link not stored

Strongest published evidence

Agentic ranks #73. Particularly useful for coding agents, browser research, and computer-use workflows.

Validate before choosing

11 published rows leave some tracked benchmark slots empty. Coding is its lowest eligible category at #95.

Source-linked · 11 displayable benchmark rows

Follow model changes

Category score record

Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.

Category scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #73 of 125Percentile 42ndWeight 22%7 benchmarksVerified
37.3
CodingRank #95 of 149Percentile 36thWeight 20%2 benchmarksVerified
30.2
ReasoningWeight 17%0 benchmarksNot measured
Not measured
MultimodalRank Not rankedWeight 12%2 benchmarksVerified
75.4
KnowledgeWeight 12%0 benchmarksNot measured
Not measured
MultilingualWeight 7%0 benchmarksNot measured
Not measured
Inst. FollowingWeight 5%0 benchmarksNot measured
Not measured
MathWeight 5%0 benchmarksNot measured
Not measured

11 of 671 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How much of this is verified

Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.

  1. Agentic7/7 verified
  2. Coding2/2 verified
  3. ReasoningNot measured
  4. Multimodal2/2 verified
  5. KnowledgeNot measured
  6. MultilingualNot measured
  7. Inst. FollowingNot measured
  8. MathNot measured
Verified sourceProvisionalNot measured

Capability shape

Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.

Step 3.7 Flash category percentile values

  • Agentic42nd percentile
  • Coding36th percentile
  • ReasoningNot eligible
  • MultimodalNot eligible
  • KnowledgeNot eligible
  • MultilingualNot eligible
  • Instruction followingNot eligible
  • MathNot eligible

The dashed outline is median of 6 nearest peers.

Eligible category ranks

  1. Agentic#73/125
  2. Coding#95/149
  3. ReasoningNot ranked
  4. MultimodalNot ranked
  5. KnowledgeNot ranked
  6. MultilingualNot ranked
  7. Inst. FollowingNot ranked
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

Benchmark ledger

Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.

Coding2 rows
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore56.3%Versus best verified row

Best verified: Claude Opus 5.5 · 89.9%

Gap33.6 behindWeight26% ref. weight
Terminal-Bench 2.1Score59.5%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap33.3 behindWeightScored in Agentic
Agentic7 rows
Agentic benchmark values, best verified comparison, weight, and source status
Terminal-Bench 2.1Score59.5%Versus best verified row

Best verified: SWE-2 · 92.8%

Gap33.3 behindWeight8% ref. weight
BrowseCompScore75.8%Versus best verified row

Best verified: Atria Dawn Preview · 92.5%

Gap16.7 behindWeight8% ref. weight
ToolathlonScore49.5%Versus best verified row

Best verified: Muse Spark 1.1 · 75.6%

Gap26.1 behindWeight3% ref. weight
HLE w/ toolsHumanity's Last Exam with toolsScore47.2%Versus best verified row

Best verified: Claude Opus 5.5 · 67.7%

Gap20.5 behindWeight3% ref. weight
DeepSearchQAScore92.8%Versus best verified row

Best verified: Atria Dawn Preview · 96.0%

Gap3.2 behindWeight2% ref. weight
Claw-EvalScore67.1%Versus best verified row

Best verified: Ornith-1.5-397B · 81.4%

Gap14.3 behindWeightDisplay only
Gert LabsGert Labs Composite Game BenchmarkScore51.57%Versus best verified row

Best verified: Claude Opus 4.8 · 72.97%

Gap21.4 behindWeightDisplay only
Benchmark exact
Multimodal2 rows
Multimodal benchmark values, best verified comparison, weight, and source status
SimpleVQAScore79.2%Versus best verified row

Best verified: Qwen3.7 Plus · 81.7%

Gap2.5 behindWeightDisplay only
V*Score95.3%Versus best verified row

Best verified: Qwen3.6 Plus · 96.9%

Gap1.6 behindWeightDisplay only

Bars run 0–100; the dark tick marks the best source-verified value

All 11 rows

What it costs to get this score

Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.

Current modelExplore all models

Step 3.7 Flash · 43.7 score · $0.67 blended per million tokens

The chart opens on the current model. Scroll horizontally to inspect the full price axis.

30405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierStep 3.7 Flash

Horizontal: blended price per million tokens, log scale · Vertical: public score

Lineage

The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.

  1. Feb 1, 2026

    Step 3.5 Flash

    Score 42.1 · $0.1 / $0.3

  2. May 29, 2026 · you are here

    Step 3.7 Flash

    Score 43.7 · $0.2 / $1.15

Base entry

Radar

Step 3.7 Flash release history

Full release history

Radar confirmed these at the source. Use Step 3.7 Flash in your work? Explore Radar to follow supported changes and choose your alerts.

Radar

Spec sheet

Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.

API model ID
Not published
Context window
256K
Maximum output
Not sourced yet
Knowledge cutoff
Not sourced yet
Input modalities
Not sourced yet
Output modalities
Not sourced yet
Parameters
Not sourced yet
Availability
Not sourced yet
Cloud regions
Not tracked yet
Lifecycle
Current
API capabilities
Tool calling, structured outputs, and batch support are not tracked yet
Prompt caching
Not documented in the pricing record
Self-host
Open weights available; hardware estimate not sourced
Rate limits
Not tracked yet

How to read this profile

The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.

Step 3.7 Flash ranks #123 of 221 on the public leaderboard with a score of 43.74/100. It does not yet have enough sourced coverage for a verified position.

Step 3.7 Flash is a open weight model with a 256K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.

Official exact-value snapshot from StepFun's May 29, 2026 Step 3.7 Flash launch page and model card. BenchLM maps only the directly comparable public values; Step-SWE-Bench, ResearchRubrics, HR-Bench, VisualProbe, and the separate Hugging Face HLE 48.1 row remain out of schema or setup-ambiguous for now.

Its explicit predecessor is Step 3.5 Flash. 11 of 671 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.

Its strongest eligible category is Agentic at #73, while its lowest eligible position is Coding at #95. particularly useful for coding agents, browser research, and computer-use workflows.

Last updated October 14, 2026. Runtime fields remain blank until a sourced snapshot exists.

Deployment options

Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.

Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.

Estimate VRAM from known parameters

Questions

How does Step 3.7 Flash perform overall in AI benchmarks?

Step 3.7 Flash ranks #123 out of 221 models on the public BenchAlign leaderboard, with a score of 43.74/100. Its evidence status is Estimated, and this profile shows 11 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.

Is Step 3.7 Flash good for coding and programming?

Step 3.7 Flash ranks #95 out of 149 eligible models for coding and programming, with a public category score of 30.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Step 3.7 Flash good for agentic tool use and computer tasks?

Step 3.7 Flash ranks #73 out of 125 eligible models for agentic tool use and computer tasks, with a public category score of 37.3/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.

Is Step 3.7 Flash good for multimodal and grounded tasks?

Step 3.7 Flash has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.

Is Step 3.7 Flash open source?

Step 3.7 Flash is an open-weight model from StepFun. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.

Does Step 3.7 Flash have full benchmark coverage on BenchLM?

No. Step 3.7 Flash currently has 28 source-displayable rows across 671 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.

What is the context window size of Step 3.7 Flash?

Step 3.7 Flash has a reported context window of 256K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.

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Compare Step 3.7 Flash with every tracked model934 comparisons