Third-party benchmark aggregation page: a total score of 61.4/100, a public rank of #50/218, and coding, Agent, knowledge, mathematics, and pricing data.
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Start free brief BenchLM Leaderboard Radar Compare Benchmarks Models Research Newsletter Tools Search ⌘ K / Browse Models Gemini 3.7 Flash Gemini 3.7 Flash Current Released Aug 13, 2026 Proprietary Reasoning 1M context Google DeepMind Gemini 3.7 Flash model card
Released Aug 13, 2026 — see all recent releases
DECISION READING Gemini 3.7 Flash scores 61.4 out of 100 and ranks #50 of 218. This profile shows 15 source-displayable benchmark rows; its strongest eligible category is Coding at #12. API pricing is $0.75 input and $3.75 output per million tokens.
Data as of August 15, 2026 · How the score is built
BENCHLM SCORE
61.4
0 50 100
Public #50 of 218
Position in the ranked field
218 ranked median 52.7 Compare Gemini 3.7 Flash Find alternatives Strongest published evidence
Coding ranks #12. Particularly well-suited for software development and code generation tasks.
Validate before choosing
15 published rows leave some tracked benchmark slots empty. Knowledge is its lowest eligible category at #32.
Read this first. The public rank is available, but this profile does not yet have enough sourced coverage for a verified position.
On this page Decision Capability Cost Evidence Specs Ledger Lineage Notes FAQ
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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
61.4 /100
field median 58.2
#50 of 218 ranked models
PRICE
$0.75 input / $3.75 output
input median $1
blended $2.25
SPEED
340 tok/s
field median 94 tok/s
First token 9.83 s
CONTEXT
1M tokens
field median 200,000
Maximum output length is tracked separately
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.
AGENTIC CODING REASONING KNOWLEDGE MATH MULTILINGUAL MULTIMODAL INSTRUCTION FOLLOWING Eligible category ranks Agentic #25/130 Coding #12/135 Reasoning Not ranked Knowledge #32/57 Math Not ranked Multilingual Not ranked Multimodal Not ranked Inst. Following Not ranked Top decile Top quartile Mid-field Not eligible 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.
Explore all models Current model Gemini 3.7 Flash · 61.4 score · $2.25 blended per million tokens 40 50 60 70 80 90 $0.50 $1 $5 $10 $25 ↘ frontier Gemini 3.7 Flash
Horizontal: blended price per million tokens, log scale · Vertical: public score
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.
Agentic 5/5 verified Coding 3/3 verified Reasoning 1/1 verified Knowledge 2/2 verified Math Not measured Multilingual Not measured Multimodal 4/4 verified Inst. Following Not measured Verified source Provisional Not measured 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 gemini-3.7-flash Google Gemini 3.7 Flash model documentation Context window 1M Google Gemini 3.7 Flash model documentation Maximum output Not sourced yet Knowledge cutoff Not sourced yet Input modalities text, image, video, audio, pdf Google Gemini 3.7 Flash model documentation Output modalities text Google Gemini 3.7 Flash model documentation Parameters Not disclosed by the provider Availability Gemini API · Google AI Studio · Google Antigravity · Gemini Enterprise Agent Platform · Gemini Enterprise · Gemini app via Spark Google Gemini 3.7 Flash launch Cloud regions Not tracked yet Lifecycle active Google Gemini 3.7 Flash model documentation API capabilities Tool calling, structured outputs, and batch support are not tracked yet Prompt caching Not documented in the pricing record Google: Introducing Gemini 3.7 Flash Self-host Weights are not published Rate limits Not tracked yet 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 Category Score Rank Percentile Weight Benchmarks Evidence
Agentic 58.0 #25 of 130 81st 22% 5 benchmarks Verified
Coding 66.4 #12 of 135 92nd 20% 3 benchmarks Verified
Reasoning Score pending Not ranked Not available 17% 1 benchmark Verified
Knowledge 67.4 #32 of 57 45th 12% 2 benchmarks Verified
Math Not measured Not ranked Not available 5% 0 benchmarks Not measured
Multilingual Not measured Not ranked Not available 7% 0 benchmarks Not measured
Multimodal 76.9 Not ranked Not available 12% 4 benchmarks Verified
Inst. Following Not measured Not ranked Not available 5% 0 benchmarks Not measured 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.
Coding 3 rows Coding benchmark values, best verified comparison, weight, and source status Benchmark Score Versus best verified row Gap Weight Evidence
FrontierCode 1.1 Main 43.6%
Best verified: Claude Fable 5 · 53.5%
9.9 behind Display only Provider exact Google DeepMind: Gemini 3.7 Flash model card
deepSwe 65.3%
Best verified: GPT-5.6 Sol · 72.7%
7.4 behind Display only Provider exact Google DeepMind: Gemini 3.7 Flash model card
Terminal-Bench 2.1 Terminal-Bench 2.1 (provider run) 85.8%
Best verified: GLM-5.3 · 88.2%
2.4 behind Display only Provider exact Google DeepMind: Gemini 3.7 Flash model card Agentic 5 rows Reasoning 1 row Knowledge 2 rows Multimodal 4 rows Lineage
The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
December 2025
Gemini 3 Flash
Score 59.7 · $0.5 / $3
May 19, 2026
Gemini 3.5 Flash
Score 64.7 · $1.5 / $9
Jul 21, 2026
Gemini 3.6 Flash
Score 75.5 · $1.5 / $7.5
Aug 13, 2026 · you are here
Gemini 3.7 Flash
Score 61.4 · $0.75 / $3.75
Base entry
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.
Gemini 3.7 Flash ranks #50 of 218 on the public leaderboard with a score of 61.36/100. It does not yet have enough sourced coverage for a verified position.
Gemini 3.7 Flash is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Available as the stable gemini-3.7-flash model through the Gemini API and Google AI Studio, and through Google Antigravity, Gemini Enterprise Agent Platform, Gemini Enterprise, and Gemini Spark. Google documents text, image, video, audio, and PDF input; text output; a 1,048,576-token input limit; and a 65,536-token output limit.
Its explicit predecessor is Gemini 3.6 Flash. 15 of 437 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #12, while its lowest eligible position is Knowledge at #32. particularly well-suited for software development and code generation tasks.
RADAR Gemini 3.7 Flash release history Full release history Gemini 3.7 Flash released
Google · Model release
Source confirmed Aug 13, 2026 Frequently asked questions How does Gemini 3.7 Flash perform overall in AI benchmarks? + Is Gemini 3.7 Flash good for knowledge and understanding? + Is Gemini 3.7 Flash good for coding and programming? + Is Gemini 3.7 Flash good for reasoning and logic? + Is Gemini 3.7 Flash good for agentic tool use and computer tasks? + Is Gemini 3.7 Flash good for multimodal and grounded tasks? + Does Gemini 3.7 Flash have full benchmark coverage on BenchLM? + What is the context window size of Gemini 3.7 Flash? +
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Last updated August 15, 2026. Runtime fields remain blank until a sourced snapshot exists.
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Models tracked 394 Benchmarks 437 Data refreshed August 15, 2026
Tracked means a model profile exists. Supported positions have sufficiently diverse direct evidence. Estimated positions remain ranked with wider uncertainty while evidence is incomplete.
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Raw benchmark rows stay exact; composite rankings use disclosed missing-data priors. © 2026 BenchLM.
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Gemini 3.7 Flash