LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

Gemini 3.6 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 3.6 Flash Replace GPT-5.2
Gemini 3.6 FlashGoogle
Coding
48.3
Overall
34.0
Output $/M
$3.75
71
GPT-5.2OpenAI
Coding
58.9
Overall
30.4
Output $/M
$14.00
12
vs boards won of 83 shared

Decision reading

Pick GPT-5.2 for coding: it scores 58.9 on the Vibe Coding Index against 48.3 for Gemini 3.6 Flash.

Pick Gemini 3.6 Flash when output tokens cost 3.7x less, or when a solved task costs $1.49 against $1.91.

Model AGemini 3.6 FlashGoogle48.3/1001 independent benchmark$1.49 per solved taskModel BGPT-5.2OpenAI58.9/1002 independent benchmarks$1.91 per solved task
Shared results
83
Gemini 3.6 Flash only
24
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 3.6 Flash 48.3 from 1 benchmark, GPT-5.2 58.9 from 2 benchmarks.
Widest category
Agentic work, 15.6 points apart on average over 4 shared benchmarks.
Widest single gap
SimpleQA Verified: Gemini 3.6 Flash 66.2% against GPT-5.2 37.1%, 29.1 points apart on a 0 to 100 scale.
Output price
Gemini 3.6 Flash $3.75 against GPT-5.2 $14.00 per million output tokens, 3.7x apart.
Context window
Gemini 3.6 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 3.6 FlashBarsGPT-5.2Ties
Coding72
Intelligence20
Agentic work40
Reasoning131
Math33
Knowledge92
Web design70
General264
All shared boards7112
CodingLike-for-likeFour of these boards feed the Vibe Coding Index72
Coding benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 FlashGPT-5.2Leader
SWE-bench VerifiedNot measured72.8%Only GPT-5.2 measured
SWE-bench MultilingualNot measured66.7%Only GPT-5.2 measured
LMArena WebDev15381417Gemini 3.6 Flash
AA Coding Index69.2Not measuredOnly Gemini 3.6 Flash measured
LiveCodeBench (Vals AI)88.1%85.4%Gemini 3.6 Flash
SWE-bench Verified (Vals AI)79.6%75.8%Gemini 3.6 Flash
Vibe Code Bench (Vals AI)64.0%53.5%Gemini 3.6 Flash
Code migration (Vals AI)30.9%Not measuredOnly Gemini 3.6 Flash measured
ProgramBench (Vals AI)0.0%Not measuredOnly Gemini 3.6 Flash measured
IOI (Vals AI)35.1%Not measuredOnly Gemini 3.6 Flash measured
Terminal-Bench 2.1 (Vals AI)73.8%Not measuredOnly Gemini 3.6 Flash measured
CyberBench (Vals AI)45.4%Not measuredOnly Gemini 3.6 Flash measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GPT-5.2 measured
SciCode53.4%Not measuredOnly Gemini 3.6 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
FrontierCode34.4%Not measuredOnly Gemini 3.6 Flash measured
GSO-BenchNot measured27.5%Only GPT-5.2 measured
WeirdML56.1%72.2%GPT-5.2
ALE-Bench715.51293.5GPT-5.2
LMArena Text: coding14911442Gemini 3.6 Flash
LMArena Text: software and IT14921434Gemini 3.6 Flash
LMArena WebDev: React1528Not measuredOnly Gemini 3.6 Flash measured
LMArena WebDev: HTML15471427Gemini 3.6 Flash
LMArena WebDev: from an image1545Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 FlashGPT-5.2Leader
AA Intelligence Index34.030.4Gemini 3.6 Flash
Epoch Capabilities Index154.5153.7Gemini 3.6 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
Agentic work benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 FlashGPT-5.2Leader
AA Agentic Index29.0Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building web apps11971086Gemini 3.6 Flash
Design Arena: agents building full-stack apps11811043Gemini 3.6 Flash
Design Arena: agents building mobile apps11991094Gemini 3.6 Flash
Design Arena: agents building Android apps12081064Gemini 3.6 Flash
Design Arena: agents building Godot gamesNot measured1142Only GPT-5.2 measured
Design Arena: agents building games1181Not measuredOnly Gemini 3.6 Flash measured
Design Arena: HTML slides1148Not measuredOnly Gemini 3.6 Flash measured
Design Arena: PowerPoint slides1146Not measuredOnly Gemini 3.6 Flash measured
Design Arena: spreadsheets1017Not measuredOnly Gemini 3.6 Flash measured
Finance Agent (Vals AI)56.3%Not measuredOnly Gemini 3.6 Flash measured
Tax Agent Bench (Vals AI)18.0%Not measuredOnly Gemini 3.6 Flash measured
Legal Research Bench (Vals AI)25.0%Not measuredOnly Gemini 3.6 Flash measured
Excel Modeling Benchmark (Vals AI)65.4%Not measuredOnly Gemini 3.6 Flash measured
BioMysteryBench (Vals AI)58.5%Not measuredOnly Gemini 3.6 Flash measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly Gemini 3.6 Flash measured
τ²-Bench TelecomNot measured84.8%Only GPT-5.2 measured
APEX-Agents46.9%Not measuredOnly Gemini 3.6 Flash measured
METR time horizonsNot measured75.3%Only GPT-5.2 measured
Remote Labor IndexNot measured2.5%Only GPT-5.2 measured
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 index131
Reasoning benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 FlashGPT-5.2Leader
GPQA Diamond93.4%91.7%Gemini 3.6 Flash
MMMU Pro (Vals AI)88.4%86.7%Gemini 3.6 Flash
GPQA Diamond (Artificial Analysis run)92.8%90.3%Gemini 3.6 Flash
Humanity's Last Exam (Artificial Analysis run)40.8%37.7%Gemini 3.6 Flash
GPQA Diamond (Epoch AI run)94.1%91.4%Gemini 3.6 Flash
ARC-AGI91.2%86.2%Gemini 3.6 Flash
ARC-AGI-260.4%52.9%Gemini 3.6 Flash
SimpleBenchNot measured45.8%Only GPT-5.2 measured
Chess puzzles42.0%48.0%GPT-5.2
Mystery game puzzles30.0%23.0%Gemini 3.6 Flash
EBR-benchNot measured23.0%Only GPT-5.2 measured
VPCTNot measured84.0%Only GPT-5.2 measured
LMArena Text: hard prompts14861428Gemini 3.6 Flash
LMArena Text: expert14901445Gemini 3.6 Flash
LMArena Text: hard prompts in English14841431Gemini 3.6 Flash
LMArena Vision: diagrams13141265Gemini 3.6 Flash
LMArena Vision: homework13141276Gemini 3.6 Flash
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 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 AIME94.2%96.1%GPT-5.2
FrontierMath, tiers 1 to 358.9%67.4%GPT-5.2
FrontierMath, tier 422.0%31.7%GPT-5.2
ProofBench36.0%15.0%Gemini 3.6 Flash
LMArena Text: math15081440Gemini 3.6 Flash
LMArena Text: mathematical work14921442Gemini 3.6 Flash
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index92
Knowledge benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 FlashGPT-5.2Leader
MMLU Pro89.3%86.2%Gemini 3.6 Flash
LegalBench (Vals AI)86.7%82.8%Gemini 3.6 Flash
CaseLaw (Vals AI)Not measured66.0%Only GPT-5.2 measured
CorpFin (Vals AI)63.3%65.9%GPT-5.2
TaxEval (Vals AI)74.9%75.8%GPT-5.2
MortgageTax (Vals AI)67.6%67.1%Gemini 3.6 Flash
MedQA (Vals AI)Not measured94.1%Only GPT-5.2 measured
MedCode (Vals AI)53.1%49.8%Gemini 3.6 Flash
MMLU Pro (Artificial Analysis run)Not measured87.4%Only GPT-5.2 measured
SimpleQA Verified66.2%37.1%Gemini 3.6 Flash
LMArena Text: science14891425Gemini 3.6 Flash
LMArena Text: medicine and healthcare14691425Gemini 3.6 Flash
LMArena Text: legal and government14791427Gemini 3.6 Flash
LMArena Text: business and finance14641414Gemini 3.6 Flash
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 FlashGPT-5.2Leader
Design Arena: websites13011196Gemini 3.6 Flash
Design Arena: UI components12971190Gemini 3.6 Flash
Design Arena: game dev12631196Gemini 3.6 Flash
Design Arena: data viz12891202Gemini 3.6 Flash
Design Arena: 3D12721079Gemini 3.6 Flash
Design Arena: all code categories12901171Gemini 3.6 Flash
Design Arena: SVGNot measured1137Only GPT-5.2 measured
Design Arena: ASCII art12811153Gemini 3.6 Flash
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index264
General benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 FlashGPT-5.2Leader
Public Benefits Bench (Vals AI)56.6%Not measuredOnly Gemini 3.6 Flash measured
SAGE (Vals AI)48.7%49.3%GPT-5.2
MedScribe (Vals AI)79.7%84.4%GPT-5.2
Vals Multimodal Index65.1%Not measuredOnly Gemini 3.6 Flash measured
IFBenchNot measured75.4%Only GPT-5.2 measured
Long context reasoning (AA-LCR)80.0%82.7%GPT-5.2
DTBench95.5%90.9%Gemini 3.6 Flash
LMCA44.9%43.9%Gemini 3.6 Flash
CL-benchNot measured18.2%Only GPT-5.2 measured
Furniture assembly23.3%38.3%GPT-5.2
LMArena Text14801416Gemini 3.6 Flash
LMArena Text: instruction following14671409Gemini 3.6 Flash
LMArena Text: creative writing14661376Gemini 3.6 Flash
LMArena Vision12991246Gemini 3.6 Flash
LMArena Text: English14821422Gemini 3.6 Flash
LMArena Text: non-English14701405Gemini 3.6 Flash
LMArena Text: Chinese15311447Gemini 3.6 Flash
LMArena Text: German14801444Gemini 3.6 Flash
LMArena Text: Japanese14751420Gemini 3.6 Flash
LMArena Text: Korean14291374Gemini 3.6 Flash
LMArena Text: French15031454Gemini 3.6 Flash
LMArena Text: Spanish14761413Gemini 3.6 Flash
LMArena Text: Russian14881415Gemini 3.6 Flash
LMArena Text: Polish14731426Gemini 3.6 Flash
LMArena Text: multi-turn14811419Gemini 3.6 Flash
LMArena Text: longer queries14751413Gemini 3.6 Flash
LMArena Text: writing and language14701392Gemini 3.6 Flash
LMArena Text: entertainment and media14561378Gemini 3.6 Flash
LMArena Vision: English12951243Gemini 3.6 Flash
LMArena Vision: Chinese13571305Gemini 3.6 Flash
LMArena Vision: reading text13121257Gemini 3.6 Flash
LMArena Vision: humor12891227Gemini 3.6 Flash
LMArena Vision: captioningNot measured1267Only GPT-5.2 measured
LMArena Vision: recognizing thingsNot measured1232Only GPT-5.2 measured
LMArena Vision: creative writing12781225Gemini 3.6 Flash
LMArena Document14561405Gemini 3.6 Flash
Neither model has a result on the other 10 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.6 Flash and GPT-5.2
BenchmarkGemini 3.6 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 3.6 Flash$0.0026Fits in one request
GPT-5.2$0.0088Fits in one request

Gemini 3.6 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.6 Flash$0.049Fits in one request
GPT-5.2$0.130Fits in one request

Gemini 3.6 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.6 Flash$0.188Fits in one request
GPT-5.2$0.490Fits in one request

Gemini 3.6 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 3.6 Flash and GPT-5.2
SpecificationGoogle Gemini 3.6 FlashOpenAI GPT-5.2
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJuly 21, 2026December 10, 2025
Context window1.05M400K
Input $/Mtok$0.75$1.75
Output $/Mtok$3.75$14.00
Coding index48.358.9
Independent measurements behind it12
Cost per solved task$1.49$1.91
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.6 Flash better than GPT-5.2 for coding?

Pick GPT-5.2 for coding: it scores 58.9 on the Vibe Coding Index against 48.3 for Gemini 3.6 Flash. Pick Gemini 3.6 Flash when output tokens cost 3.7x less, or when a solved task costs $1.49 against $1.91.

Which is cheaper, Gemini 3.6 Flash or GPT-5.2?

Gemini 3.6 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 3.6 Flash costs $1.49 and GPT-5.2 $1.91.

Which has the bigger context window, Gemini 3.6 Flash or GPT-5.2?

Gemini 3.6 Flash, with 1.05M tokens against 400K.

How many benchmarks is the Gemini 3.6 Flash vs GPT-5.2 comparison based on?

83 benchmarks have a result for both models as of October 21, 2026. Gemini 3.6 Flash's coding index rests on 1 independent benchmark and GPT-5.2's on 2. Where only one model has a result, the page says so instead of naming a winner.

Compare next