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Gemini 3.6 Flash vs GPT-4o (2024-08-06)

Gemini 3.6 Flash leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 34.0 to 7.7, and Gemini 3.6 Flash costs 2.7x less per output token ($3.75 vs $10.00 per million). Updated October 22, 2026; 45 benchmarks have a result for both.

Replace Gemini 3.6 Flash Replace GPT-4o (2024-08-06)
Gemini 3.6 FlashGoogle
Coding
62.5
Overall
68.3
Output $/M
$3.75
45
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
0
vs boards won of 45 shared

Gemini 3.6 Flash or GPT-4o (2024-08-06): which to pick

Only Gemini 3.6 Flash has a coding score, 62.5 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGemini 3.6 FlashGoogle62.5/1004 independent benchmarks$1.49 per solved taskModel BGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
45
Gemini 3.6 Flash only
64
GPT-4o (2024-08-06) only
13
Like-for-like categories
6 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 3.6 Flash 62.5 from 4 benchmarks, GPT-4o (2024-08-06) not benchmarked.
Widest category
Math, 54.6 points apart on average over 4 shared benchmarks.
Widest single gap
OTIS Mock AIME: Gemini 3.6 Flash 94.2% against GPT-4o (2024-08-06) 6.4%, 87.8 points apart on a 0 to 100 scale.
Output price
Gemini 3.6 Flash $3.75 against GPT-4o (2024-08-06) $10.00 per million output tokens, 2.7x apart.
Context window
Gemini 3.6 Flash takes 1.05M tokens, GPT-4o (2024-08-06) 128K.

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-4o (2024-08-06)Ties
Coding20
Intelligence10
Reasoning80
Math40
Knowledge100
General200
All shared boards450
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
Aider polyglotNot measured23.1%Only GPT-4o (2024-08-06) measured
SWE-bench LiteNot measured21.7%Only GPT-4o (2024-08-06) measured
LMArena WebDev1538Not measuredOnly Gemini 3.6 Flash measured
AA Coding Index69.2Not measuredOnly Gemini 3.6 Flash measured
LiveCodeBench (Vals AI)88.1%Not measuredOnly Gemini 3.6 Flash measured
SWE-bench Verified (Vals AI)79.6%Not measuredOnly Gemini 3.6 Flash measured
Vibe Code Bench (Vals AI)64.0%Not measuredOnly Gemini 3.6 Flash measured
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 measured31.7%Only GPT-4o (2024-08-06) measured
SciCode53.4%Not measuredOnly Gemini 3.6 Flash measured
Terminal-Bench Hard (Artificial Analysis run)Not measured8.3%Only GPT-4o (2024-08-06) measured
FrontierCode34.4%Not measuredOnly Gemini 3.6 Flash measured
WeirdML56.1%Not measuredOnly Gemini 3.6 Flash measured
ALE-Bench715.5Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: coding14911283Gemini 3.6 Flash
LMArena Text: software and IT14921278Gemini 3.6 Flash
LMArena WebDev: React1528Not measuredOnly Gemini 3.6 Flash measured
LMArena WebDev: HTML1547Not measuredOnly Gemini 3.6 Flash measured
LMArena WebDev: from an image1545Not measuredOnly Gemini 3.6 Flash measured
SciCode10.8%Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
AA Intelligence Index34.07.7Gemini 3.6 Flash
Epoch Capabilities Index154.5Not measuredOnly Gemini 3.6 Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
Agentic work benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
AA Agentic Index29.0Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building web apps1197Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building full-stack apps1181Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building mobile apps1198Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building Android apps1204Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building games1180Not measuredOnly Gemini 3.6 Flash measured
Design Arena: HTML slides1099Not measuredOnly Gemini 3.6 Flash measured
Design Arena: PowerPoint slides1121Not measuredOnly Gemini 3.6 Flash measured
Design Arena: spreadsheets1071Not 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 measured28.9%Only GPT-4o (2024-08-06) measured
APEX-Agents46.9%Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
Reasoning benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
GPQA Diamond93.4%Not measuredOnly Gemini 3.6 Flash measured
MMMU Pro (Vals AI)88.4%64.0%Gemini 3.6 Flash
GPQA Diamond (Artificial Analysis run)92.8%52.1%Gemini 3.6 Flash
Humanity's Last Exam (Artificial Analysis run)40.8%2.3%Gemini 3.6 Flash
GPQA Diamond (Epoch AI run)94.1%49.2%Gemini 3.6 Flash
ARC-AGI91.2%Not measuredOnly Gemini 3.6 Flash measured
ARC-AGI-260.4%Not measuredOnly Gemini 3.6 Flash measured
SimpleBenchNot measured17.8%Only GPT-4o (2024-08-06) measured
Chess puzzles42.0%6.0%Gemini 3.6 Flash
Mystery game puzzles30.0%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: hard prompts14861264Gemini 3.6 Flash
LMArena Text: expert14901241Gemini 3.6 Flash
LMArena Text: hard prompts in English14841277Gemini 3.6 Flash
LMArena Vision: diagrams1314Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: homework1314Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index40
Math benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
AIMENot measured14.0%Only GPT-4o (2024-08-06) measured
MATH 500 (Vals AI)Not measured75.2%Only GPT-4o (2024-08-06) measured
MGSM (Vals AI)Not measured90.7%Only GPT-4o (2024-08-06) measured
OTIS Mock AIME94.2%6.4%Gemini 3.6 Flash
FrontierMath, tiers 1 to 358.9%0.4%Gemini 3.6 Flash
FrontierMath, tier 422.0%Not measuredOnly Gemini 3.6 Flash measured
ProofBench36.0%Not measuredOnly Gemini 3.6 Flash measured
MATH level 5Not measured53.3%Only GPT-4o (2024-08-06) measured
LMArena Text: math15081285Gemini 3.6 Flash
LMArena Text: mathematical work14921283Gemini 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 index100
Knowledge benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
MMLU Pro89.3%74.1%Gemini 3.6 Flash
LegalBench (Vals AI)86.7%80.1%Gemini 3.6 Flash
CorpFin (Vals AI)63.3%39.4%Gemini 3.6 Flash
TaxEval (Vals AI)74.9%71.1%Gemini 3.6 Flash
MortgageTax (Vals AI)67.6%61.0%Gemini 3.6 Flash
MedQA (Vals AI)Not measured88.2%Only GPT-4o (2024-08-06) measured
MedCode (Vals AI)53.1%Not measuredOnly Gemini 3.6 Flash measured
SimpleQA Verified66.2%26.0%Gemini 3.6 Flash
MMLUNot measured84.3%Only GPT-4o (2024-08-06) measured
LMArena Text: science14891274Gemini 3.6 Flash
LMArena Text: medicine and healthcare14691252Gemini 3.6 Flash
LMArena Text: legal and government14791275Gemini 3.6 Flash
LMArena Text: business and finance14641232Gemini 3.6 Flash
FACTS Benchmark Suite65.3%Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 4 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
Design Arena: websites1300Not measuredOnly Gemini 3.6 Flash measured
Design Arena: UI components1294Not measuredOnly Gemini 3.6 Flash measured
Design Arena: game dev1263Not measuredOnly Gemini 3.6 Flash measured
Design Arena: data viz1289Not measuredOnly Gemini 3.6 Flash measured
Design Arena: 3D1271Not measuredOnly Gemini 3.6 Flash measured
Design Arena: all code categories1289Not measuredOnly Gemini 3.6 Flash measured
Design Arena: ASCII art1281Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index200
General benchmarks for Gemini 3.6 Flash and GPT-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
Public Benefits Bench (Vals AI)56.6%Not measuredOnly Gemini 3.6 Flash measured
SAGE (Vals AI)48.7%Not measuredOnly Gemini 3.6 Flash measured
MedScribe (Vals AI)79.7%Not measuredOnly Gemini 3.6 Flash measured
Vals Multimodal Index65.1%Not measuredOnly Gemini 3.6 Flash measured
IFBenchNot measured36.0%Only GPT-4o (2024-08-06) measured
Long context reasoning (AA-LCR)80.0%41.0%Gemini 3.6 Flash
DTBench95.5%Not measuredOnly Gemini 3.6 Flash measured
LMCA44.9%Not measuredOnly Gemini 3.6 Flash measured
Furniture assembly23.3%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text14801283Gemini 3.6 Flash
LMArena Text: instruction following14671267Gemini 3.6 Flash
LMArena Text: creative writing14661274Gemini 3.6 Flash
LMArena Vision12991065Gemini 3.6 Flash
LMArena Text: English14821297Gemini 3.6 Flash
LMArena Text: non-English14701262Gemini 3.6 Flash
LMArena Text: Chinese15311254Gemini 3.6 Flash
LMArena Text: German14801257Gemini 3.6 Flash
LMArena Text: Japanese14751234Gemini 3.6 Flash
LMArena Text: Korean14291218Gemini 3.6 Flash
LMArena Text: French15031263Gemini 3.6 Flash
LMArena Text: Spanish14761269Gemini 3.6 Flash
LMArena Text: Russian14881272Gemini 3.6 Flash
LMArena Text: Polish1473Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: multi-turn14811279Gemini 3.6 Flash
LMArena Text: longer queries14751283Gemini 3.6 Flash
LMArena Text: writing and language14701290Gemini 3.6 Flash
LMArena Text: entertainment and media14561267Gemini 3.6 Flash
LMArena Vision: English12951072Gemini 3.6 Flash
LMArena Vision: Chinese13571009Gemini 3.6 Flash
LMArena Vision: reading text1312Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: humor1289Not measuredOnly Gemini 3.6 Flash measured
LMArena Vision: creative writing1278Not measuredOnly Gemini 3.6 Flash measured
LMArena Document1456Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 13 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-4o (2024-08-06)
BenchmarkGemini 3.6 FlashGPT-4o (2024-08-06)Leader
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-4o (2024-08-06)$0.0075Fits 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-4o (2024-08-06)$0.155Fits 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-4o (2024-08-06)$0.600Exceeds the context window

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-4o (2024-08-06)
SpecificationGoogle Gemini 3.6 FlashOpenAI GPT-4o (2024-08-06)
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJuly 21, 2026August 6, 2024
Context window1.05M128K
Input $/Mtok$0.75$2.50
Output $/Mtok$3.75$10.00
Coding index62.5Not benchmarked
Independent measurements behind it40
Cost per solved task$1.49Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.6 Flash better than GPT-4o (2024-08-06) for coding?

Only Gemini 3.6 Flash has a coding score, 62.5 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, Gemini 3.6 Flash or GPT-4o (2024-08-06)?

Gemini 3.6 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-4o (2024-08-06) costs $2.50 and $10.00. Cost per solved task is known for Gemini 3.6 Flash only.

Which has the bigger context window, Gemini 3.6 Flash or GPT-4o (2024-08-06)?

Gemini 3.6 Flash, with 1.05M tokens against 128K.

How many benchmarks is the Gemini 3.6 Flash vs GPT-4o (2024-08-06) comparison based on?

45 benchmarks have a result for both models as of October 22, 2026. Gemini 3.6 Flash's coding index rests on 4 independent benchmarks and GPT-4o (2024-08-06)'s on 0. Where only one model has a result, the page says so instead of naming a winner.

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