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Gemini 3.5 Flash vs Gemini 3.7 Flash

Gemini 3.7 Flash leads Gemini 3.5 Flash on coding, 58.0 to 39.8 on the Vibe Coding Index, and Gemini 3.7 Flash costs 2.4x less per output token ($3.75 vs $9.00 per million). Updated October 22, 2026; 99 benchmarks have a result for both.

Replace Gemini 3.5 Flash Replace Gemini 3.7 Flash
Gemini 3.5 FlashGoogle
Coding
39.8
Overall
63.8
Output $/M
$9.00
7
Gemini 3.7 FlashGoogle
Coding
58.0
Overall
65.7
Output $/M
$3.75
91
vs boards won of 99 shared, 1 tied

Gemini 3.5 Flash or Gemini 3.7 Flash: which to pick

Pick Gemini 3.7 Flash for coding: it scores 58.0 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash.

Pick Gemini 3.5 Flash for a lower cost per solved task ($1.21 against $1.78) and work measured by ALE-Bench or LMArena Vision: homework, where it leads.

Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved task
Shared results
99
Gemini 3.5 Flash only
16
Gemini 3.7 Flash only
16
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Gemini 3.5 Flash 39.8 from 4 benchmarks, Gemini 3.7 Flash 58.0 from 6 benchmarks.
Widest category
Agentic work, 8.5 points apart on average over 12 shared benchmarks.
Widest single gap
APEX-Agents: Gemini 3.5 Flash 27.5% against Gemini 3.7 Flash 67.8%, 40.3 points apart on a 0 to 100 scale.
Output price
Gemini 3.5 Flash $9.00 against Gemini 3.7 Flash $3.75 per million output tokens, 2.4x apart.
Context window
Both take 1.05M tokens.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGemini 3.5 FlashBarsGemini 3.7 FlashTies
Coding1151 tie
Intelligence02
Agentic work012
Reasoning113
Math07
Knowledge29
Web design08
General325
All shared boards7911 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index115
Coding benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
LiveBench codingNot measured80.5%Only Gemini 3.7 Flash measured
LMArena WebDev14991591Gemini 3.7 Flash
AA Coding IndexNot measured71.5Only Gemini 3.7 Flash measured
LiveCodeBench (Vals AI)87.6%88.7%Gemini 3.7 Flash
SWE-bench Verified (Vals AI)78.8%80.8%Gemini 3.7 Flash
Terminal-Bench 4 (Vals AI)6.1%12.1%Gemini 3.7 Flash
Vibe Code Bench (Vals AI)48.7%70.4%Gemini 3.7 Flash
Code migration (Vals AI)26.8%34.8%Gemini 3.7 Flash
ProgramBench (Vals AI)0.0%0.0%Tie
IOI (Vals AI)Not measured67.8%Only Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)74.2%77.5%Gemini 3.7 Flash
SkillsBench (Vals AI)52.7%65.9%Gemini 3.7 Flash
CyberBench (Vals AI)Not measured43.8%Only Gemini 3.7 Flash measured
SciCode53.9%59.8%Gemini 3.7 Flash
Terminal-Bench Hard (Artificial Analysis run)46.2%Not measuredOnly Gemini 3.5 Flash measured
FrontierCodeNot measured43.6%Only Gemini 3.7 Flash measured
FrontierSWENot measured20.3%Only Gemini 3.7 Flash measured
WeirdML62.6%Not measuredOnly Gemini 3.5 Flash measured
ALE-Bench911.0904.3Gemini 3.5 Flash
LMArena Text: coding14931499Gemini 3.7 Flash
LMArena Text: software and IT14941498Gemini 3.7 Flash
LMArena WebDev: React14951587Gemini 3.7 Flash
LMArena WebDev: HTML15221593Gemini 3.7 Flash
LMArena WebDev: from an image15041599Gemini 3.7 Flash
SciCode12.3%13.8%Gemini 3.7 Flash
Neither model has a result on the other 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
AA Intelligence Index33.639.6Gemini 3.7 Flash
Epoch Capabilities Index154.9158.0Gemini 3.7 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index012
Agentic work benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
Design Arena: agents building web apps12021223Gemini 3.7 Flash
Design Arena: agents building full-stack apps11971208Gemini 3.7 Flash
Design Arena: agents building mobile apps11751230Gemini 3.7 Flash
Design Arena: agents building Android apps11841242Gemini 3.7 Flash
Design Arena: agents building Godot games10981264Gemini 3.7 Flash
Design Arena: agents building games11801235Gemini 3.7 Flash
Design Arena: HTML slides1082Not measuredOnly Gemini 3.5 Flash measured
Design Arena: PowerPoint slides1153Not measuredOnly Gemini 3.5 Flash measured
Design Arena: spreadsheetsNot measured1094Only Gemini 3.7 Flash measured
LiveBench researchNot measured76.5%Only Gemini 3.7 Flash measured
LiveBench browserNot measured56.0%Only Gemini 3.7 Flash measured
LiveBench long agenticNot measured28.3%Only Gemini 3.7 Flash measured
SREBench (Vals AI)Not measured4.6%Only Gemini 3.7 Flash measured
Finance Agent (Vals AI)57.9%59.0%Gemini 3.7 Flash
Tax Agent Bench (Vals AI)21.6%22.8%Gemini 3.7 Flash
Legal Research Bench (Vals AI)30.8%34.6%Gemini 3.7 Flash
Excel Modeling Benchmark (Vals AI)63.5%71.3%Gemini 3.7 Flash
Terminal-Bench-Science (Vals AI)5.7%7.1%Gemini 3.7 Flash
τ²-Bench Telecom95.6%Not measuredOnly Gemini 3.5 Flash measured
APEX-Agents27.5%67.8%Gemini 3.7 Flash
Remote Labor IndexNot measured5.0%Only Gemini 3.7 Flash measured
Vending-Bench 2$5,396Not measuredOnly Gemini 3.5 Flash measured
MCP Atlas83.6%Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 19 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index113
Reasoning benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
GPQA Diamond92.7%93.9%Gemini 3.7 Flash
LiveBench reasoningNot measured87.8%Only Gemini 3.7 Flash measured
MMMU Pro (Vals AI)88.3%89.0%Gemini 3.7 Flash
GPQA Diamond (Artificial Analysis run)92.2%94.5%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)42.7%47.9%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)92.8%94.8%Gemini 3.7 Flash
ARC-AGI92.5%95.5%Gemini 3.7 Flash
ARC-AGI-272.1%84.6%Gemini 3.7 Flash
SimpleBench76.7%Not measuredOnly Gemini 3.5 Flash measured
Chess puzzles45.0%66.0%Gemini 3.7 Flash
Mystery game puzzles32.0%37.0%Gemini 3.7 Flash
EBR-bench4.8%Not measuredOnly Gemini 3.5 Flash measured
LMArena Text: hard prompts14881495Gemini 3.7 Flash
LMArena Text: expert14951512Gemini 3.7 Flash
LMArena Text: hard prompts in English14831487Gemini 3.7 Flash
LMArena Vision: diagrams13231329Gemini 3.7 Flash
LMArena Vision: homework13301320Gemini 3.5 Flash
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index07
Math benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
OTIS Mock AIME95.6%97.2%Gemini 3.7 Flash
FrontierMath, tiers 1 to 362.8%71.6%Gemini 3.7 Flash
FrontierMath, tier 426.8%36.6%Gemini 3.7 Flash
ProofBench31.0%58.0%Gemini 3.7 Flash
LMArena Text: math15041511Gemini 3.7 Flash
LMArena Text: mathematical work14951502Gemini 3.7 Flash
MathArena24.7%25.9%Gemini 3.7 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index29
Knowledge benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
MMLU Pro89.5%90.1%Gemini 3.7 Flash
LegalBench (Vals AI)83.6%87.3%Gemini 3.7 Flash
CorpFin (Vals AI)64.7%Not measuredOnly Gemini 3.5 Flash measured
TaxEval (Vals AI)74.4%74.7%Gemini 3.7 Flash
MortgageTax (Vals AI)68.1%66.7%Gemini 3.5 Flash
MedCode (Vals AI)55.8%53.4%Gemini 3.5 Flash
SimpleQA Verified66.2%69.2%Gemini 3.7 Flash
LMArena Text: science14951511Gemini 3.7 Flash
LMArena Text: medicine and healthcare14831494Gemini 3.7 Flash
LMArena Text: legal and government14881496Gemini 3.7 Flash
LMArena Text: business and finance14671479Gemini 3.7 Flash
FACTS Benchmark Suite63.1%71.2%Gemini 3.7 Flash
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
Design Arena: websites12671303Gemini 3.7 Flash
Design Arena: UI components12701295Gemini 3.7 Flash
Design Arena: game dev12631317Gemini 3.7 Flash
Design Arena: data viz12371315Gemini 3.7 Flash
Design Arena: 3D12431306Gemini 3.7 Flash
Design Arena: all code categories12661307Gemini 3.7 Flash
Design Arena: SVG12531284Gemini 3.7 Flash
Design Arena: ASCII art12541278Gemini 3.7 Flash
LiveBench designNot measured73.2%Only Gemini 3.7 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index325
General benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
LiveBench data analysisNot measured68.0%Only Gemini 3.7 Flash measured
Public Benefits Bench (Vals AI)59.5%Not measuredOnly Gemini 3.5 Flash measured
SAGE (Vals AI)49.9%49.2%Gemini 3.5 Flash
MedScribe (Vals AI)76.6%83.9%Gemini 3.7 Flash
Vals Multimodal Index62.9%Not measuredOnly Gemini 3.5 Flash measured
IFBench76.3%Not measuredOnly Gemini 3.5 Flash measured
Long context reasoning (AA-LCR)74.3%83.0%Gemini 3.7 Flash
DTBench94.7%96.8%Gemini 3.7 Flash
LMCA47.1%50.4%Gemini 3.7 Flash
Surface Evolver Bench58.1%Not measuredOnly Gemini 3.5 Flash measured
Furniture assemblyNot measured26.7%Only Gemini 3.7 Flash measured
LMArena Text14821489Gemini 3.7 Flash
LMArena Text: instruction following14671484Gemini 3.7 Flash
LMArena Text: creative writing14701488Gemini 3.7 Flash
LMArena Vision13081314Gemini 3.7 Flash
LMArena Text: English14811483Gemini 3.7 Flash
LMArena Text: non-English14751487Gemini 3.7 Flash
LMArena Text: Chinese15271552Gemini 3.7 Flash
LMArena Text: German14941506Gemini 3.7 Flash
LMArena Text: Japanese14861511Gemini 3.7 Flash
LMArena Text: Korean14481481Gemini 3.7 Flash
LMArena Text: French14901500Gemini 3.7 Flash
LMArena Text: Spanish14801495Gemini 3.7 Flash
LMArena Text: Russian14931515Gemini 3.7 Flash
LMArena Text: Polish15161503Gemini 3.5 Flash
LMArena Text: multi-turn14811485Gemini 3.7 Flash
LMArena Text: longer queries14831492Gemini 3.7 Flash
LMArena Text: writing and language14781491Gemini 3.7 Flash
LMArena Text: entertainment and media14591477Gemini 3.7 Flash
LMArena Vision: English13051309Gemini 3.7 Flash
LMArena Vision: Chinese13771394Gemini 3.7 Flash
LMArena Vision: reading text13171322Gemini 3.7 Flash
LMArena Vision: humor13211299Gemini 3.5 Flash
LMArena Vision: creative writing13011312Gemini 3.7 Flash
LMArena Document1463Not measuredOnly Gemini 3.5 Flash measured
EQ-Bench 41087Not measuredOnly Gemini 3.5 Flash measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.5 Flash and Gemini 3.7 Flash
BenchmarkGemini 3.5 FlashGemini 3.7 FlashLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Gemini 3.5 Flash$0.0060Fits in one request
Gemini 3.7 Flash$0.0026Fits in one request

Gemini 3.7 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.5 Flash$0.102Fits in one request
Gemini 3.7 Flash$0.049Fits in one request

Gemini 3.7 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.5 Flash$0.390Fits in one request
Gemini 3.7 Flash$0.188Fits in one request

Gemini 3.7 Flash costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Gemini 3.5 Flash and Gemini 3.7 Flash
SpecificationGoogle Gemini 3.5 FlashGoogle Gemini 3.7 Flash
MakerGoogleGoogle
WeightsNo public weights listedNo public weights listed
ReleasedMay 19, 2026August 13, 2026
Context window1.05M1.05M
Input $/Mtok$1.50$0.75
Output $/Mtok$9.00$3.75
Coding index39.858.0
Independent measurements behind it46
Cost per solved task$1.21$1.78
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.5 Flash better than Gemini 3.7 Flash for coding?

Pick Gemini 3.7 Flash for coding: it scores 58.0 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash. Pick Gemini 3.5 Flash for a lower cost per solved task ($1.21 against $1.78) and work measured by ALE-Bench or LMArena Vision: homework, where it leads.

Which is cheaper, Gemini 3.5 Flash or Gemini 3.7 Flash?

Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; Gemini 3.7 Flash costs $0.75 and $3.75. Per solved SWE-bench Verified task, Gemini 3.5 Flash costs $1.21 and Gemini 3.7 Flash $1.78.

Which has the bigger context window, Gemini 3.5 Flash or Gemini 3.7 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.5 Flash vs Gemini 3.7 Flash comparison based on?

99 benchmarks have a result for both models as of October 22, 2026. Gemini 3.5 Flash's coding index rests on 4 independent benchmarks and Gemini 3.7 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-3-5-flash-vs-gemini-3-7-flash">LLMBenchmark.ai, Gemini 3.5 Flash vs Gemini 3.7 Flash</a></p>