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Head-to-head comparison

Gemini 3.7 Flash vs. Gemini 3.5 Flash

Compare published benchmark results from matching versions and cohorts, API pricing, and technical specifications. Any documented test setup differences remain visible.

shared result series
25
distinct benchmarks
25
latest retrieval
2026-09-29

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Specifications

General specifications

Release date, availability, context window, architecture, and published parameter counts at a glance. Undisclosed details remain marked as unavailable.

Specifications for Gemini 3.7 Flash and Gemini 3.5 Flash
AttributeGemini 3.7 FlashGemini 3.5 Flash
ProviderGoogleGoogle
ReleasedAug 13, 2026May 19, 2026
AvailabilityActiveActive
Model typeProprietaryProprietary
ParametersNot publishedNot published
ArchitectureNot publishedNot published
Context window1,048,576 tokens1,048,576 tokens
Knowledge cutoffMarch 2026Not published
Technical sourcesModel, Knowledge cutoffModel

Pricing

API pricing compared

The table compares official standard API rates per 1M tokens, including published cache pricing. Batch, fast, priority, regional surcharges, tool calls, and cloud platform pricing are excluded.

API pricing for Gemini 3.7 Flash and Gemini 3.5 Flash
Price typeGemini 3.7 FlashGemini 3.5 Flash
API input$0.75$1.5
API output$3.75$9
Cache read$0.07$0.15
Cache write (5 min.)Not listedNot listed
Cache write (1 hr.)Not listedNot listed
Price verified09/22/2026 Source09/22/2026 Source
Gemini 3.7 FlashGemini 3.5 Flash
API inputUSD per 1M tokens, base tier
Gemini 3.7 FlashLower price$0.75
Gemini 3.5 Flash$1.5
API outputUSD per 1M tokens, base tier
Gemini 3.7 FlashLower price$3.75
Gemini 3.5 Flash$9
Cache readUSD per 1M tokens, base tier
Gemini 3.7 FlashLower price$0.075
Gemini 3.5 Flash$0.15

Key to the marks:better valuebetter, but not conclusivetie

Pricing by provider

Direct developer pricing and provider endpoint tariffs routed through OpenRouter are listed separately. Prices are in USD per 1M tokens. Context-dependent direct tiers plus regional, Flex, Priority, and other OpenRouter tariffs remain individually identifiable.

Provider pricing for Gemini 3.7 Flash and Gemini 3.5 Flash
ModelProviderPurchase route and tariffInput per 1M tokensOutput per 1M tokensSource
Gemini 3.7 FlashGoogleDirect from developerStandard API$0.75$3.75Source09/22/2026
GoogleVia OpenRoutergoogle-vertex/global$0.75$3.75Source10/02/2026
GoogleVia OpenRoutergoogle-vertex/global/flexLowest listed price: $0.375Lowest listed price: $1.875Source10/02/2026
GoogleVia OpenRoutergoogle-vertex/global/priority$1.35$6.75Source10/02/2026
Google AI StudioVia OpenRoutergoogle-ai-studio$0.75$3.75Source10/02/2026
Google AI StudioVia OpenRoutergoogle-ai-studio/flexLowest listed price: $0.375Lowest listed price: $1.875Source10/02/2026
Google AI StudioVia OpenRoutergoogle-ai-studio/priority$1.35$6.75Source10/02/2026
Gemini 3.5 FlashGoogleDirect from developerStandard API$1.5$9Source09/22/2026
GoogleVia OpenRoutergoogle-vertex/global$1.5$9Source10/02/2026
GoogleVia OpenRoutergoogle-vertex/global/flexLowest listed price: $0.75Lowest listed price: $4.5Source10/02/2026
GoogleVia OpenRoutergoogle-vertex/global/priority$2.7$16.2Source10/02/2026
GoogleVia OpenRoutergoogle-vertex/us$1.65$9.9Source10/02/2026
Google AI StudioVia OpenRoutergoogle-ai-studio$1.5$9Source10/02/2026
Google AI StudioVia OpenRoutergoogle-ai-studio/flexLowest listed price: $0.75Lowest listed price: $4.5Source10/02/2026
Google AI StudioVia OpenRoutergoogle-ai-studio/priority$2.7$16.2Source10/02/2026

Performance

Shared benchmarks

Only published results with the same benchmark version, task, metric, and comparison cohort are paired. Different reasoning levels, agents, harnesses, or output limits appear directly in the table.

Capability profile from matched benchmarks

Each axis averages directly matched benchmark families. A value of 100 means the stronger value within this pair, not a universal quality score.

255075100CodingReasoningMathematicsKnowledgeFinanceLegalAgentic tasksMultimodal
Gemini 3.7 Flash
Gemini 3.5 Flash
Coding: 100 / 84.8 (6 benchmark families)
Reasoning: 100 / 98.7 (1 benchmark family)
Mathematics: 100 / 53.4 (1 benchmark family)
Knowledge: 100 / 99.3 (1 benchmark family)
Finance: 99.6 / 95.9 (5 benchmark families)
Legal: 100 / 71.1 (3 benchmark families)
Agentic tasks: 100 / 87.8 (2 benchmark families)
Multimodal: 100 / 99.2 (1 benchmark family)

25 matched rows from 24 benchmark families were considered. The radar shows 8 of 12 comparable categories.

Gemini 3.7 FlashGemini 3.5 Flash
Code MigrationOverall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner34.8 %
Gemini 3.5 Flash26.745 %
EMBOverall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner71.326 %
Gemini 3.5 Flash63.548 %
Finance Agent (v2)Overall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner59.042 %
Gemini 3.5 Flash57.861 %
GPQA DiamondOverall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner93.94 %
Gemini 3.5 Flash92.676 %
Harvey's Legal Agent BenchmarkOverall · Task fully resolved. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner8.75 %
Gemini 3.5 Flash2.5 %
Legal Research BenchOverall · All-pass. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner34.615 %
Gemini 3.5 Flash30.769 %
LegalBenchOverall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner87.256 %
Gemini 3.5 Flash83.602 %
LiveCodeBench v6Overall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner88.652 %
Gemini 3.5 Flash87.604 %
MedCodeOverall. Higher is better. No documented setup difference
Gemini 3.7 Flash53.39 %
Gemini 3.5 FlashWinner55.825 %
MedScribeOverall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner83.942 %
Gemini 3.5 Flash76.574 %
MMLU-ProOverall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner90.121 %
Gemini 3.5 Flash89.515 %
MMMU-ProOverall. Higher is better. No documented setup difference
Gemini 3.7 FlashWinner88.96 %
Gemini 3.5 Flash88.266 %

Key to the marks:better valuebetter, but not conclusivetie

Benchmark scores for Gemini 3.7 Flash and Gemini 3.5 Flash
Benchmark and taskGemini 3.7 FlashGemini 3.5 FlashSource
Code MigrationOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner34.8 %
26.745 %
Vals AI
Source details
Data as of: 09/27/2026
EMBOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner71.326 %
63.548 %
Vals AI
Source details
Data as of: 09/27/2026
Finance Agent (v2)Overall
Test details
No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better
Winner59.042 %
57.861 %
Vals AI
Source details
Data as of: 09/27/2026
GPQA DiamondOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner93.94 %
92.676 %
Vals AI
Source details
Data as of: 09/01/2026
Harvey's Legal Agent BenchmarkOverall · Task fully resolved
Test details
No documented difference in the test setupVersion: 1Metric: task resolution rateScoring: Higher is better
Winner8.75 %
2.5 %
Vals AI
Source details
Data as of: 09/27/2026
Legal Research BenchOverall · All-pass
Test details
No documented difference in the test setupVersion: 1Metric: all-pass rateScoring: Higher is better
Winner34.615 %
30.769 %
Vals AI
Source details
Data as of: 09/27/2026
LegalBenchOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner87.256 %
83.602 %
Vals AI
Source details
Data as of: 09/27/2026
LiveCodeBench v6Overall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner88.652 %
87.604 %
Vals AI
Source details
Data as of: 09/01/2026
MedCodeOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
53.39 %
Winner55.825 %
Vals AI
Source details
Data as of: 09/26/2026
MedScribeOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner83.942 %
76.574 %
Vals AI
Source details
Data as of: 09/26/2026
MMLU-ProOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner90.121 %
89.515 %
Vals AI
Source details
Data as of: 09/01/2026
MMMU-ProOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner88.96 %
88.266 %
Vals AI
Source details
Data as of: 09/01/2026
MortgageTaxOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
66.654 %
Winner68.124 %
Vals AI
Source details
Data as of: 09/01/2026
ProgramBenchOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Tie0 %
Tie0 %
Vals AI
Source details
Data as of: 09/27/2026
ProofBenchOverall
Test details
No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is better
Winner58 %
31 %
Vals AI
Source details
Data as of: 09/28/2026
SAGEOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
49.232 %
Winner49.885 %
Vals AI
Source details
Data as of: 09/26/2026
SkillsBenchOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is betterSettings: Harness: OpenHands
Winner65.891 %
52.737 %
Vals AI
Source details
Data as of: 09/27/2026
SWE-bench VerifiedOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner80.8 %
78.8 %
Vals AI
Source details
Data as of: 09/01/2026
Tax Agent BenchOverall
Test details
No documented difference in the test setupVersion: 1Metric: accuracyScoring: Higher is better
Winner57.665 %
53.526 %
Vals AI
Source details
Data as of: 09/27/2026
TaxEval v2Overall
Test details
No documented difference in the test setupVersion: 2Metric: accuracyScoring: Higher is better
Winner74.734 %
74.366 %
Vals AI
Source details
Data as of: 09/01/2026
Terminal-Bench 2.1Overall
Test details
No documented difference in the test setupVersion: 2.1Metric: accuracyScoring: Higher is better
Winner77.528 %
74.157 %
Vals AI
Source details
Data as of: 09/27/2026
Terminal-Bench 4.0Overall
Test details
No documented difference in the test setupVersion: 4.0Metric: accuracyScoring: Higher is better
Winner6.061 %
4.04 %
Vals AI
Source details
Data as of: 09/27/2026
Terminal-Bench ScienceOverall
Test details
No documented difference in the test setupVersion: 0.1Metric: accuracyScoring: Higher is better
Winner5.714 %
4.286 %
Vals AI
Source details
Data as of: 09/27/2026
Vals IndexOverall
Test details
No documented difference in the test setupVersion: 2Metric: weighted index scoreScoring: Higher is better
Winner59.307 %
53.079 %
Vals AI
Source details
Data as of: 09/27/2026
Vibe Code Bench v1.1Overall
Test details
No documented difference in the test setupVersion: 1.1Metric: accuracyScoring: Higher is betterSettings: Harness: OpenHands
Winner70.395 %
48.683 %
Vals AI
Source details
Data as of: 09/27/2026

Key to the marks:better valuebetter, but not conclusivetie

Our model tests

Our tests

Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.

Pelican on a bicycle

A community classic for free-form SVG drawing.

Gemini 3.7 Flash

API access was unavailable for this run. The model was not evaluated.

Reasoning (requested): high

First attempt
Run date
7 Sept 2026
API provider
openrouter
Requested API model
google/gemini-3.7-flash
Reasoning setting
high
Pinned endpoint
Google AI Studio | google/gemini-3.7-flash-20260813
Temperature
Provider default
Token limit including reasoning
8,192 tokens
Test protocol
community-visual-tests-v1
Technical checks
Not run

Not yet visually reviewed. A successful recording does not confirm correct physics or full compliance with the prompt.

Gemini 3.5 Flash

API access was unavailable for this run. The model was not evaluated.

Reasoning (requested): high

First attempt
Run date
7 Sept 2026
API provider
openrouter
Requested API model
google/gemini-3.5-flash
Reasoning setting
high
Pinned endpoint
Google AI Studio | google/gemini-3.5-flash-20260519
Temperature
Provider default
Token limit including reasoning
8,192 tokens
Test protocol
community-visual-tests-v1
Technical checks
Not run

Not yet visually reviewed. A successful recording does not confirm correct physics or full compliance with the prompt.

Prompt and test conditions

Generate an SVG of a pelican riding a bicycle

Token limit including reasoning: 8,192 tokens

Task origin (Simon Willison)

How to read this comparison

Winning one benchmark is not an overall verdict

Your workload, budget, and required context length matter most. A coding benchmark says little about visual understanding or agent performance.

The standard price table uses direct developer rates. The provider comparison labels OpenRouter endpoints, regions, and special tariffs separately.

Every result links to its measurement source and retrieval date. Labels distinguish vendor reports, official benchmark leaderboards, and independent evaluations. Disputed or archived results are excluded.

More matchups

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View the complete LLM comparison