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Gemini 2.5 Pro vs Gemini 3.7 Flash

Gemini 3.7 Flash leads Gemini 2.5 Pro on coding, 58.0 to 19.1 on the Vibe Coding Index, and Gemini 3.7 Flash costs 2.7x less per output token ($3.75 vs $10.00 per million). Updated October 22, 2026; 67 benchmarks have a result for both.

Gemini 2.5 ProGoogle
Coding
19.1
Overall
41.8
Output $/M
$10.00
1
Gemini 3.7 FlashGoogle
Coding
58.0
Overall
65.7
Output $/M
$3.75
66
vs boards won of 67 shared

Gemini 2.5 Pro 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 19.1 for Gemini 2.5 Pro.

Pick Gemini 2.5 Pro for a lower cost per solved task ($0.64 against $1.78) and work measured by MortgageTax (Vals AI), where it leads.

Shared results
67
Gemini 2.5 Pro only
23
Gemini 3.7 Flash only
47
Like-for-like categories
7 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 2.5 Pro 19.1 from 3 benchmarks, Gemini 3.7 Flash 58.0 from 6 benchmarks.
Widest category
Coding, 36.3 points apart on average over 9 shared benchmarks.
Widest single gap
ARC-AGI-2: Gemini 2.5 Pro 4.9% against Gemini 3.7 Flash 84.6%, 79.7 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against Gemini 3.7 Flash $3.75 per million output tokens, 2.7x 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 2.5 ProBarsGemini 3.7 FlashTies
Coding09
Intelligence02
Reasoning010
Math05
Knowledge16
Web design06
General028
All shared boards166
CodingLike-for-likeSix of these boards feed the Vibe Coding Index09
Coding benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
SWE-bench Verified53.6%Not measuredOnly Gemini 2.5 Pro measured
LiveBench codingNot measured80.5%Only Gemini 3.7 Flash measured
LMArena WebDev12261591Gemini 3.7 Flash
AA Coding Index33.371.5Gemini 3.7 Flash
LiveCodeBench (Vals AI)Not measured88.7%Only Gemini 3.7 Flash measured
SWE-bench Verified (Vals AI)54.4%80.8%Gemini 3.7 Flash
Terminal-Bench 4 (Vals AI)Not measured12.1%Only Gemini 3.7 Flash measured
Vibe Code Bench (Vals AI)0.4%70.4%Gemini 3.7 Flash
Code migration (Vals AI)Not measured34.8%Only Gemini 3.7 Flash measured
ProgramBench (Vals AI)Not measured0.0%Only Gemini 3.7 Flash measured
IOI (Vals AI)Not measured67.8%Only Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)Not measured77.5%Only Gemini 3.7 Flash measured
SkillsBench (Vals AI)Not measured65.9%Only Gemini 3.7 Flash measured
CyberBench (Vals AI)Not measured43.8%Only Gemini 3.7 Flash measured
LiveCodeBench (Artificial Analysis run)80.1%Not measuredOnly Gemini 2.5 Pro measured
SciCode46.3%59.8%Gemini 3.7 Flash
Terminal-Bench Hard (Artificial Analysis run)26.5%Not measuredOnly Gemini 2.5 Pro measured
Terminal-Bench32.6%Not measuredOnly Gemini 2.5 Pro measured
FrontierCodeNot measured43.6%Only Gemini 3.7 Flash measured
FrontierSWENot measured20.3%Only Gemini 3.7 Flash measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro measured
WeirdML54.0%Not measuredOnly Gemini 2.5 Pro measured
ALE-BenchNot measured904.3Only Gemini 3.7 Flash measured
LMArena Text: coding14521499Gemini 3.7 Flash
LMArena Text: software and IT14591498Gemini 3.7 Flash
LMArena WebDev: ReactNot measured1587Only Gemini 3.7 Flash measured
LMArena WebDev: HTML12351593Gemini 3.7 Flash
LMArena WebDev: from an image12851599Gemini 3.7 Flash
SciCodeNot measured13.8%Only Gemini 3.7 Flash measured
Neither model has a result on the other 10 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
AA Intelligence Index16.139.6Gemini 3.7 Flash
Epoch Capabilities Index145.1158.0Gemini 3.7 Flash
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index24 boards, none shared
Agentic work benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
AA Agentic Index1.6Not measuredOnly Gemini 2.5 Pro measured
Design Arena: agents building web appsNot measured1223Only Gemini 3.7 Flash measured
Design Arena: agents building full-stack appsNot measured1208Only Gemini 3.7 Flash measured
Design Arena: agents building mobile appsNot measured1229Only Gemini 3.7 Flash measured
Design Arena: agents building Android appsNot measured1243Only Gemini 3.7 Flash measured
Design Arena: agents building Godot gamesNot measured1264Only Gemini 3.7 Flash measured
Design Arena: agents building gamesNot measured1235Only Gemini 3.7 Flash measured
Design Arena: spreadsheetsNot measured1058Only 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)Not measured59.0%Only Gemini 3.7 Flash measured
Tax Agent Bench (Vals AI)Not measured22.8%Only Gemini 3.7 Flash measured
Legal Research Bench (Vals AI)Not measured34.6%Only Gemini 3.7 Flash measured
Excel Modeling Benchmark (Vals AI)Not measured71.3%Only Gemini 3.7 Flash measured
Terminal-Bench-Science (Vals AI)Not measured7.1%Only Gemini 3.7 Flash measured
τ²-Bench Telecom54.1%Not measuredOnly Gemini 2.5 Pro measured
APEX-AgentsNot measured67.8%Only Gemini 3.7 Flash measured
Remote Labor IndexNot measured5.0%Only Gemini 3.7 Flash measured
GDPval23.3%Not measuredOnly Gemini 2.5 Pro measured
DeepResearch Bench41.5%Not measuredOnly Gemini 2.5 Pro measured
Vending-Bench 2$574Not measuredOnly Gemini 2.5 Pro measured
BrowseComp-Plus29.5%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 17 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index010
Reasoning benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
GPQA DiamondNot measured93.9%Only Gemini 3.7 Flash measured
LiveBench reasoningNot measured87.8%Only Gemini 3.7 Flash measured
MMMU Pro (Vals AI)Not measured89.0%Only Gemini 3.7 Flash measured
GPQA Diamond (Artificial Analysis run)84.4%94.5%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)22.5%47.9%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)85.3%94.8%Gemini 3.7 Flash
ARC-AGI41.0%95.5%Gemini 3.7 Flash
ARC-AGI-24.9%84.6%Gemini 3.7 Flash
Chess puzzlesNot measured66.0%Only Gemini 3.7 Flash measured
Mystery game puzzlesNot measured37.0%Only Gemini 3.7 Flash measured
LMArena Text: hard prompts14551495Gemini 3.7 Flash
LMArena Text: expert14521512Gemini 3.7 Flash
LMArena Text: hard prompts in English14531487Gemini 3.7 Flash
LMArena Vision: diagrams12741329Gemini 3.7 Flash
LMArena Vision: homework12811320Gemini 3.7 Flash
Kagi LLM Benchmark70.3%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index05
Math benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
AA Math Index87.7Not measuredOnly Gemini 2.5 Pro measured
AIME 2025 (Artificial Analysis run)87.7%Not measuredOnly Gemini 2.5 Pro measured
OTIS Mock AIME84.7%97.2%Gemini 3.7 Flash
FrontierMath, tiers 1 to 324.6%71.6%Gemini 3.7 Flash
FrontierMath, tier 40.0%36.6%Gemini 3.7 Flash
ProofBenchNot measured58.0%Only Gemini 3.7 Flash measured
LMArena Text: math14501511Gemini 3.7 Flash
LMArena Text: mathematical work14541502Gemini 3.7 Flash
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index16
Knowledge benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
MMLU ProNot measured90.1%Only Gemini 3.7 Flash measured
LegalBench (Vals AI)Not measured87.3%Only Gemini 3.7 Flash measured
CaseLaw (Vals AI)63.9%Not measuredOnly Gemini 2.5 Pro measured
CorpFin (Vals AI)60.8%Not measuredOnly Gemini 2.5 Pro measured
TaxEval (Vals AI)Not measured74.7%Only Gemini 3.7 Flash measured
MortgageTax (Vals AI)68.9%66.7%Gemini 2.5 Pro
MedCode (Vals AI)50.6%53.4%Gemini 3.7 Flash
MMLU Pro (Artificial Analysis run)86.2%Not measuredOnly Gemini 2.5 Pro measured
SimpleQA VerifiedNot measured69.2%Only Gemini 3.7 Flash measured
LMArena Text: science14801511Gemini 3.7 Flash
LMArena Text: medicine and healthcare14761494Gemini 3.7 Flash
LMArena Text: legal and government14801496Gemini 3.7 Flash
LMArena Text: business and finance14391479Gemini 3.7 Flash
FACTS Benchmark Suite61.5%71.2%Gemini 3.7 Flash
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
Design Arena: websites11671303Gemini 3.7 Flash
Design Arena: UI components11371296Gemini 3.7 Flash
Design Arena: game dev11111317Gemini 3.7 Flash
Design Arena: data viz12221315Gemini 3.7 Flash
Design Arena: 3D10801307Gemini 3.7 Flash
Design Arena: all code categories11521308Gemini 3.7 Flash
Design Arena: SVGNot measured1283Only Gemini 3.7 Flash measured
Design Arena: ASCII artNot measured1276Only Gemini 3.7 Flash measured
LiveBench designNot measured73.2%Only Gemini 3.7 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index028
General benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 3.7 FlashLeader
LiveBench data analysisNot measured68.0%Only Gemini 3.7 Flash measured
SAGE (Vals AI)41.9%49.2%Gemini 3.7 Flash
MedScribe (Vals AI)73.5%83.9%Gemini 3.7 Flash
IFBench48.7%Not measuredOnly Gemini 2.5 Pro measured
Long context reasoning (AA-LCR)69.0%83.0%Gemini 3.7 Flash
DTBench82.4%96.8%Gemini 3.7 Flash
LMCA34.8%50.4%Gemini 3.7 Flash
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
Furniture assemblyNot measured26.7%Only Gemini 3.7 Flash measured
LMArena Text14581489Gemini 3.7 Flash
LMArena Text: instruction following14371484Gemini 3.7 Flash
LMArena Text: creative writing14541488Gemini 3.7 Flash
LMArena Vision12631314Gemini 3.7 Flash
LMArena Text: English14581483Gemini 3.7 Flash
LMArena Text: non-English14521487Gemini 3.7 Flash
LMArena Text: Chinese15071552Gemini 3.7 Flash
LMArena Text: German14871506Gemini 3.7 Flash
LMArena Text: Japanese14611511Gemini 3.7 Flash
LMArena Text: Korean14341481Gemini 3.7 Flash
LMArena Text: French14731500Gemini 3.7 Flash
LMArena Text: Spanish14741495Gemini 3.7 Flash
LMArena Text: Russian14611515Gemini 3.7 Flash
LMArena Text: Polish14791503Gemini 3.7 Flash
LMArena Text: multi-turn14531485Gemini 3.7 Flash
LMArena Text: longer queries14491492Gemini 3.7 Flash
LMArena Text: writing and language14541491Gemini 3.7 Flash
LMArena Text: entertainment and media14411477Gemini 3.7 Flash
LMArena Vision: English12611309Gemini 3.7 Flash
LMArena Vision: Chinese13001394Gemini 3.7 Flash
LMArena Vision: reading text12701322Gemini 3.7 Flash
LMArena Vision: humor12621299Gemini 3.7 Flash
LMArena Vision: captioning1304Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: recognizing things1283Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: creative writing12651312Gemini 3.7 Flash
LMArena Document1421Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 2.5 Pro and Gemini 3.7 Flash
BenchmarkGemini 2.5 ProGemini 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 2.5 Pro$0.0063Fits 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 2.5 Pro$0.092Fits 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 2.5 Pro$0.350Fits 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 2.5 Pro and Gemini 3.7 Flash
SpecificationGoogle Gemini 2.5 ProGoogle Gemini 3.7 Flash
MakerGoogleGoogle
WeightsNo public weights listedNo public weights listed
ReleasedJune 17, 2025August 13, 2026
Context window1.05M1.05M
Input $/Mtok$1.25$0.75
Output $/Mtok$10.00$3.75
Coding index19.158.0
Independent measurements behind it36
Cost per solved task$0.64$1.78
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro 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 19.1 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro for a lower cost per solved task ($0.64 against $1.78) and work measured by MortgageTax (Vals AI), where it leads.

Which is cheaper, Gemini 2.5 Pro or Gemini 3.7 Flash?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Gemini 3.7 Flash costs $0.75 and $3.75. Per solved SWE-bench Verified task, Gemini 2.5 Pro costs $0.64 and Gemini 3.7 Flash $1.78.

Which has the bigger context window, Gemini 2.5 Pro or Gemini 3.7 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 2.5 Pro vs Gemini 3.7 Flash comparison based on?

67 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 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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