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Gemini 3.7 Flash vs GPT-5.2

Updated October 21, 2026. 83 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Gemini 3.7 Flash Replace GPT-5.2
Gemini 3.7 FlashGoogle
Coding
69.9
Overall
39.6
Output $/M
$3.75
77
GPT-5.2OpenAI
Coding
58.9
Overall
30.4
Output $/M
$14.00
6
vs boards won of 83 shared

Decision reading

Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 58.9 for GPT-5.2.

Pick GPT-5.2 when what matters is ALE-Bench or TaxEval (Vals AI), where it leads.

Model AGemini 3.7 FlashGoogle69.9/1002 independent benchmarks$1.78 per solved taskModel BGPT-5.2OpenAI58.9/1002 independent benchmarks$1.91 per solved task
Shared results
83
Gemini 3.7 Flash only
29
GPT-5.2 only
28
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 3.7 Flash 69.9 from 2 benchmarks, GPT-5.2 58.9 from 2 benchmarks.
Widest category
Web design, 17.0 points apart on average over 8 shared benchmarks.
Widest single gap
ProofBench: Gemini 3.7 Flash 58.0% against GPT-5.2 15.0%, 43.0 points apart on a 0 to 100 scale.
Output price
Gemini 3.7 Flash $3.75 against GPT-5.2 $14.00 per million output tokens, 3.7x apart.
Context window
Gemini 3.7 Flash takes 1.05M tokens, GPT-5.2 400K.

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 3.7 FlashBarsGPT-5.2Ties
Coding71
Intelligence20
Agentic work60
Reasoning140
Math60
Knowledge82
Web design80
General263
All shared boards776
CodingLike-for-likeFour of these boards feed the Vibe Coding Index71
Coding benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
SWE-bench VerifiedNot measured72.8%Only GPT-5.2 measured
SWE-bench MultilingualNot measured66.7%Only GPT-5.2 measured
LiveBench coding80.5%Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev15911417Gemini 3.7 Flash
AA Coding Index71.5Not measuredOnly Gemini 3.7 Flash measured
LiveCodeBench (Vals AI)88.7%85.4%Gemini 3.7 Flash
SWE-bench Verified (Vals AI)80.8%75.8%Gemini 3.7 Flash
Terminal-Bench 4 (Vals AI)12.1%Not measuredOnly Gemini 3.7 Flash measured
Vibe Code Bench (Vals AI)70.4%53.5%Gemini 3.7 Flash
Code migration (Vals AI)34.8%Not measuredOnly Gemini 3.7 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.7 Flash measured
IOI (Vals AI)67.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench 2.1 (Vals AI)77.5%Not measuredOnly Gemini 3.7 Flash measured
SkillsBench (Vals AI)65.9%Not measuredOnly Gemini 3.7 Flash measured
CyberBench (Vals AI)43.8%Not measuredOnly Gemini 3.7 Flash measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GPT-5.2 measured
SciCode59.8%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench Hard (Artificial Analysis run)Not measured47.0%Only GPT-5.2 measured
Terminal-BenchNot measured64.9%Only GPT-5.2 measured
FrontierCode43.6%Not measuredOnly Gemini 3.7 Flash measured
FrontierSWE20.3%Not measuredOnly Gemini 3.7 Flash measured
GSO-BenchNot measured27.5%Only GPT-5.2 measured
WeirdMLNot measured72.2%Only GPT-5.2 measured
ALE-Bench904.31293.5GPT-5.2
LMArena Text: coding14991442Gemini 3.7 Flash
LMArena Text: software and IT14981434Gemini 3.7 Flash
LMArena WebDev: React1587Not measuredOnly Gemini 3.7 Flash measured
LMArena WebDev: HTML15931427Gemini 3.7 Flash
LMArena WebDev: from an image1599Not measuredOnly Gemini 3.7 Flash measured
Neither model has a result on the other 9 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
AA Intelligence Index39.630.4Gemini 3.7 Flash
Epoch Capabilities Index158.0153.7Gemini 3.7 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index60
Agentic work benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
Design Arena: agents building web apps12241086Gemini 3.7 Flash
Design Arena: agents building full-stack apps12081043Gemini 3.7 Flash
Design Arena: agents building mobile apps12301094Gemini 3.7 Flash
Design Arena: agents building Android apps12471064Gemini 3.7 Flash
Design Arena: agents building Godot games12641142Gemini 3.7 Flash
Design Arena: agents building games1235Not measuredOnly Gemini 3.7 Flash measured
Design Arena: spreadsheets1028Not measuredOnly Gemini 3.7 Flash measured
LiveBench research76.5%Not measuredOnly Gemini 3.7 Flash measured
LiveBench browser56.0%Not measuredOnly Gemini 3.7 Flash measured
LiveBench long agentic28.3%Not measuredOnly Gemini 3.7 Flash measured
SREBench (Vals AI)4.6%Not measuredOnly Gemini 3.7 Flash measured
Finance Agent (Vals AI)59.0%Not measuredOnly Gemini 3.7 Flash measured
Tax Agent Bench (Vals AI)22.8%Not measuredOnly Gemini 3.7 Flash measured
Legal Research Bench (Vals AI)34.6%Not measuredOnly Gemini 3.7 Flash measured
Excel Modeling Benchmark (Vals AI)71.3%Not measuredOnly Gemini 3.7 Flash measured
Terminal-Bench-Science (Vals AI)7.1%Not measuredOnly Gemini 3.7 Flash measured
τ²-Bench TelecomNot measured84.8%Only GPT-5.2 measured
APEX-Agents67.8%Not measuredOnly Gemini 3.7 Flash measured
METR time horizonsNot measured75.3%Only GPT-5.2 measured
Remote Labor Index5.0%2.5%Gemini 3.7 Flash
GDPvalNot measured49.7%Only GPT-5.2 measured
DeepResearch BenchNot measured41.1%Only GPT-5.2 measured
Vending-Bench 2Not measured$3,591Only GPT-5.2 measured
Neither model has a result on the other 16 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index140
Reasoning benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
GPQA Diamond93.9%91.7%Gemini 3.7 Flash
LiveBench reasoning87.8%Not measuredOnly Gemini 3.7 Flash measured
MMMU Pro (Vals AI)89.0%86.7%Gemini 3.7 Flash
GPQA Diamond (Artificial Analysis run)94.5%90.3%Gemini 3.7 Flash
Humanity's Last Exam (Artificial Analysis run)47.9%37.7%Gemini 3.7 Flash
GPQA Diamond (Epoch AI run)94.8%91.4%Gemini 3.7 Flash
ARC-AGI95.5%86.2%Gemini 3.7 Flash
ARC-AGI-284.6%52.9%Gemini 3.7 Flash
SimpleBenchNot measured45.8%Only GPT-5.2 measured
Chess puzzles66.0%48.0%Gemini 3.7 Flash
Mystery game puzzles37.0%23.0%Gemini 3.7 Flash
EBR-benchNot measured23.0%Only GPT-5.2 measured
VPCTNot measured84.0%Only GPT-5.2 measured
LMArena Text: hard prompts14951428Gemini 3.7 Flash
LMArena Text: expert15121445Gemini 3.7 Flash
LMArena Text: hard prompts in English14871431Gemini 3.7 Flash
LMArena Vision: diagrams13291265Gemini 3.7 Flash
LMArena Vision: homework13201276Gemini 3.7 Flash
Neither model has a result on the other 3 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index60
Math benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
AIMENot measured96.9%Only GPT-5.2 measured
MGSM (Vals AI)Not measured94.0%Only GPT-5.2 measured
AA Math IndexNot measured99.0Only GPT-5.2 measured
AIME 2025 (Artificial Analysis run)Not measured99.0%Only GPT-5.2 measured
OTIS Mock AIME97.2%96.1%Gemini 3.7 Flash
FrontierMath, tiers 1 to 371.6%67.4%Gemini 3.7 Flash
FrontierMath, tier 436.6%31.7%Gemini 3.7 Flash
ProofBench58.0%15.0%Gemini 3.7 Flash
LMArena Text: math15111440Gemini 3.7 Flash
LMArena Text: mathematical work15021442Gemini 3.7 Flash
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index82
Knowledge benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
MMLU Pro90.1%86.2%Gemini 3.7 Flash
LegalBench (Vals AI)87.3%82.8%Gemini 3.7 Flash
CaseLaw (Vals AI)Not measured66.0%Only GPT-5.2 measured
CorpFin (Vals AI)Not measured65.9%Only GPT-5.2 measured
TaxEval (Vals AI)74.7%75.8%GPT-5.2
MortgageTax (Vals AI)66.7%67.1%GPT-5.2
MedQA (Vals AI)Not measured94.1%Only GPT-5.2 measured
MedCode (Vals AI)53.4%49.8%Gemini 3.7 Flash
MMLU Pro (Artificial Analysis run)Not measured87.4%Only GPT-5.2 measured
SimpleQA Verified69.2%37.1%Gemini 3.7 Flash
LMArena Text: science15111425Gemini 3.7 Flash
LMArena Text: medicine and healthcare14941425Gemini 3.7 Flash
LMArena Text: legal and government14961427Gemini 3.7 Flash
LMArena Text: business and finance14791414Gemini 3.7 Flash
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
Design Arena: websites13041196Gemini 3.7 Flash
Design Arena: UI components12991190Gemini 3.7 Flash
Design Arena: game dev13181196Gemini 3.7 Flash
Design Arena: data viz13151202Gemini 3.7 Flash
Design Arena: 3D13081079Gemini 3.7 Flash
Design Arena: all code categories13081171Gemini 3.7 Flash
Design Arena: SVG12831137Gemini 3.7 Flash
Design Arena: ASCII art12761153Gemini 3.7 Flash
LiveBench design73.2%Not measuredOnly Gemini 3.7 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index263
General benchmarks for Gemini 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
LiveBench data analysis68.0%Not measuredOnly Gemini 3.7 Flash measured
SAGE (Vals AI)49.2%49.3%GPT-5.2
MedScribe (Vals AI)83.9%84.4%GPT-5.2
IFBenchNot measured75.4%Only GPT-5.2 measured
Long context reasoning (AA-LCR)83.0%82.7%Gemini 3.7 Flash
DTBench96.8%90.9%Gemini 3.7 Flash
LMCA50.4%43.9%Gemini 3.7 Flash
CL-benchNot measured18.2%Only GPT-5.2 measured
Furniture assembly26.7%38.3%GPT-5.2
LMArena Text14891416Gemini 3.7 Flash
LMArena Text: instruction following14841409Gemini 3.7 Flash
LMArena Text: creative writing14881376Gemini 3.7 Flash
LMArena Vision13141246Gemini 3.7 Flash
LMArena Text: English14831422Gemini 3.7 Flash
LMArena Text: non-English14871405Gemini 3.7 Flash
LMArena Text: Chinese15521447Gemini 3.7 Flash
LMArena Text: German15061444Gemini 3.7 Flash
LMArena Text: Japanese15111420Gemini 3.7 Flash
LMArena Text: Korean14811374Gemini 3.7 Flash
LMArena Text: French15001454Gemini 3.7 Flash
LMArena Text: Spanish14951413Gemini 3.7 Flash
LMArena Text: Russian15151415Gemini 3.7 Flash
LMArena Text: Polish15031426Gemini 3.7 Flash
LMArena Text: multi-turn14851419Gemini 3.7 Flash
LMArena Text: longer queries14921413Gemini 3.7 Flash
LMArena Text: writing and language14911392Gemini 3.7 Flash
LMArena Text: entertainment and media14771378Gemini 3.7 Flash
LMArena Vision: English13091243Gemini 3.7 Flash
LMArena Vision: Chinese13941305Gemini 3.7 Flash
LMArena Vision: reading text13221257Gemini 3.7 Flash
LMArena Vision: humor12991227Gemini 3.7 Flash
LMArena Vision: captioningNot measured1267Only GPT-5.2 measured
LMArena Vision: recognizing thingsNot measured1232Only GPT-5.2 measured
LMArena Vision: creative writing13121225Gemini 3.7 Flash
LMArena DocumentNot measured1405Only GPT-5.2 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 3.7 Flash and GPT-5.2
BenchmarkGemini 3.7 FlashGPT-5.2Leader
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 3.7 Flash$0.0026Fits in one request
GPT-5.2$0.0088Fits in one request

Gemini 3.7 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.7 Flash$0.049Fits in one request
GPT-5.2$0.130Fits in one request

Gemini 3.7 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.7 Flash$0.188Fits in one request
GPT-5.2$0.490Fits 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 3.7 Flash and GPT-5.2
SpecificationGoogle Gemini 3.7 FlashOpenAI GPT-5.2
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedAugust 13, 2026December 10, 2025
Context window1.05M400K
Input $/Mtok$0.75$1.75
Output $/Mtok$3.75$14.00
Coding index69.958.9
Independent measurements behind it22
Cost per solved task$1.78$1.91
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.7 Flash better than GPT-5.2 for coding?

Pick Gemini 3.7 Flash for coding: it scores 69.9 on the Vibe Coding Index against 58.9 for GPT-5.2. Pick GPT-5.2 when what matters is ALE-Bench or TaxEval (Vals AI), where it leads.

Which is cheaper, Gemini 3.7 Flash or GPT-5.2?

Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-5.2 costs $1.75 and $14.00. Per solved SWE-bench Verified task, Gemini 3.7 Flash costs $1.78 and GPT-5.2 $1.91.

Which has the bigger context window, Gemini 3.7 Flash or GPT-5.2?

Gemini 3.7 Flash, with 1.05M tokens against 400K.

How many benchmarks is the Gemini 3.7 Flash vs GPT-5.2 comparison based on?

83 benchmarks have a result for both models as of October 21, 2026. Gemini 3.7 Flash's coding index rests on 2 independent benchmarks and GPT-5.2's on 2. Where only one model has a result, the page says so instead of naming a winner.

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