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Gemini 3.6 Flash vs GPT-4.1 Nano

Updated October 21, 2026. 55 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-4.1 Nano
Gemini 3.6 FlashGoogle
Coding
48.3
Overall
34.0
Output $/M
$3.75
55
GPT-4.1 NanoOpenAI
Coding
8.9
Overall
7.8
Output $/M
$0.40
0
vs boards won of 55 shared

Decision reading

Pick Gemini 3.6 Flash for coding: it scores 48.3 on the Vibe Coding Index against 8.9 for GPT-4.1 Nano.

Pick GPT-4.1 Nano when output tokens cost 9.4x less.

Model AGemini 3.6 FlashGoogle48.3/1001 independent benchmark$1.49 per solved taskModel BGPT-4.1 NanoOpenAI8.9/1001 independent benchmarkNo cost per solved task
Shared results
55
Gemini 3.6 Flash only
52
GPT-4.1 Nano only
14
Like-for-like categories
7 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-4.1 Nano 8.9 from 1 benchmark.
Widest category
Math, 46.8 points apart on average over 3 shared benchmarks.
Widest single gap
ARC-AGI: Gemini 3.6 Flash 91.2% against GPT-4.1 Nano 0.0%, 91.2 points apart on a 0 to 100 scale.
Output price
Gemini 3.6 Flash $3.75 against GPT-4.1 Nano $0.40 per million output tokens, 9.4x apart.
Context window
Gemini 3.6 Flash takes 1.05M tokens, GPT-4.1 Nano 1.05M.

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-4.1 NanoTies
Coding50
Intelligence20
Reasoning110
Math30
Knowledge100
Web design60
General180
All shared boards550
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
Coding benchmarks for Gemini 3.6 Flash and GPT-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
Aider polyglotNot measured8.9%Only GPT-4.1 Nano measured
LMArena WebDev1538Not measuredOnly Gemini 3.6 Flash measured
AA Coding Index69.211.1Gemini 3.6 Flash
LiveCodeBench (Vals AI)88.1%42.7%Gemini 3.6 Flash
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 measured32.6%Only GPT-4.1 Nano measured
SciCode53.4%Not measuredOnly Gemini 3.6 Flash measured
Terminal-Bench Hard (Artificial Analysis run)Not measured3.8%Only GPT-4.1 Nano measured
FrontierCode34.4%Not measuredOnly Gemini 3.6 Flash measured
WeirdML56.1%19.0%Gemini 3.6 Flash
ALE-Bench715.5Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: coding14911306Gemini 3.6 Flash
LMArena Text: software and IT14921305Gemini 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
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.6 Flash and GPT-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
AA Intelligence Index34.07.8Gemini 3.6 Flash
Epoch Capabilities Index154.5129.5Gemini 3.6 Flash
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-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
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 apps1199Not measuredOnly Gemini 3.6 Flash measured
Design Arena: agents building Android apps1208Not measuredOnly Gemini 3.6 Flash 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 measured17.3%Only GPT-4.1 Nano measured
APEX-Agents46.9%Not measuredOnly Gemini 3.6 Flash measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index110
Reasoning benchmarks for Gemini 3.6 Flash and GPT-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
GPQA Diamond93.4%50.8%Gemini 3.6 Flash
MMMU Pro (Vals AI)88.4%55.0%Gemini 3.6 Flash
GPQA Diamond (Artificial Analysis run)92.8%51.2%Gemini 3.6 Flash
Humanity's Last Exam (Artificial Analysis run)40.8%3.8%Gemini 3.6 Flash
GPQA Diamond (Epoch AI run)94.1%48.9%Gemini 3.6 Flash
ARC-AGI91.2%0.0%Gemini 3.6 Flash
ARC-AGI-260.4%0.0%Gemini 3.6 Flash
Chess puzzles42.0%0.0%Gemini 3.6 Flash
Mystery game puzzles30.0%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: hard prompts14861286Gemini 3.6 Flash
LMArena Text: expert14901271Gemini 3.6 Flash
LMArena Text: hard prompts in English14841293Gemini 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 index30
Math benchmarks for Gemini 3.6 Flash and GPT-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
AIMENot measured26.5%Only GPT-4.1 Nano measured
MATH 500 (Vals AI)Not measured80.2%Only GPT-4.1 Nano measured
MGSM (Vals AI)Not measured69.3%Only GPT-4.1 Nano measured
AA Math IndexNot measured24.0Only GPT-4.1 Nano measured
AIME 2025 (Artificial Analysis run)Not measured24.0%Only GPT-4.1 Nano measured
OTIS Mock AIME94.2%28.9%Gemini 3.6 Flash
FrontierMath, tiers 1 to 358.9%Not measuredOnly Gemini 3.6 Flash measured
FrontierMath, tier 422.0%Not measuredOnly Gemini 3.6 Flash measured
ProofBench36.0%Not measuredOnly Gemini 3.6 Flash measured
MATH level 5Not measured70.0%Only GPT-4.1 Nano measured
LMArena Text: math15081274Gemini 3.6 Flash
LMArena Text: mathematical work14921274Gemini 3.6 Flash
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index100
Knowledge benchmarks for Gemini 3.6 Flash and GPT-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
MMLU Pro89.3%63.5%Gemini 3.6 Flash
LegalBench (Vals AI)86.7%61.1%Gemini 3.6 Flash
CorpFin (Vals AI)63.3%42.1%Gemini 3.6 Flash
TaxEval (Vals AI)74.9%60.8%Gemini 3.6 Flash
MortgageTax (Vals AI)67.6%52.8%Gemini 3.6 Flash
MedQA (Vals AI)Not measured68.2%Only GPT-4.1 Nano measured
MedCode (Vals AI)53.1%Not measuredOnly Gemini 3.6 Flash measured
MMLU Pro (Artificial Analysis run)Not measured65.7%Only GPT-4.1 Nano measured
SimpleQA Verified66.2%6.0%Gemini 3.6 Flash
LMArena Text: science14891297Gemini 3.6 Flash
LMArena Text: medicine and healthcare14691276Gemini 3.6 Flash
LMArena Text: legal and government14791300Gemini 3.6 Flash
LMArena Text: business and finance14641267Gemini 3.6 Flash
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for Gemini 3.6 Flash and GPT-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
Design Arena: websites1301973Gemini 3.6 Flash
Design Arena: UI components1297916Gemini 3.6 Flash
Design Arena: game dev1263971Gemini 3.6 Flash
Design Arena: data viz1289891Gemini 3.6 Flash
Design Arena: 3D1272925Gemini 3.6 Flash
Design Arena: all code categories1290963Gemini 3.6 Flash
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 index180
General benchmarks for Gemini 3.6 Flash and GPT-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
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 measured32.0%Only GPT-4.1 Nano measured
Long context reasoning (AA-LCR)80.0%20.3%Gemini 3.6 Flash
DTBench95.5%52.5%Gemini 3.6 Flash
LMCA44.9%5.5%Gemini 3.6 Flash
Fiction.LiveBenchNot measured25.0%Only GPT-4.1 Nano measured
Furniture assembly23.3%Not measuredOnly Gemini 3.6 Flash measured
LMArena Text14801285Gemini 3.6 Flash
LMArena Text: instruction following14671266Gemini 3.6 Flash
LMArena Text: creative writing14661260Gemini 3.6 Flash
LMArena Vision12991063Gemini 3.6 Flash
LMArena Text: English14821303Gemini 3.6 Flash
LMArena Text: non-English14701260Gemini 3.6 Flash
LMArena Text: Chinese15311270Gemini 3.6 Flash
LMArena Text: German14801288Gemini 3.6 Flash
LMArena Text: Japanese14751198Gemini 3.6 Flash
LMArena Text: Korean1429Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: French1503Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Spanish1476Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: Russian14881261Gemini 3.6 Flash
LMArena Text: Polish1473Not measuredOnly Gemini 3.6 Flash measured
LMArena Text: multi-turn14811277Gemini 3.6 Flash
LMArena Text: longer queries14751283Gemini 3.6 Flash
LMArena Text: writing and language14701261Gemini 3.6 Flash
LMArena Text: entertainment and media14561243Gemini 3.6 Flash
LMArena Vision: English12951101Gemini 3.6 Flash
LMArena Vision: Chinese1357Not measuredOnly Gemini 3.6 Flash measured
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 12 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-4.1 Nano
BenchmarkGemini 3.6 FlashGPT-4.1 NanoLeader
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-4.1 Nano$0.0003Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

Gemini 3.6 Flash$0.049Fits in one request
GPT-4.1 Nano$0.0062Fits in one request

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

Gemini 3.6 Flash$0.188Fits in one request
GPT-4.1 Nano$0.024Fits in one request

GPT-4.1 Nano 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-4.1 Nano
SpecificationGoogle Gemini 3.6 FlashOpenAI GPT-4.1 Nano
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJuly 21, 2026April 14, 2025
Context window1.05M1.05M
Input $/Mtok$0.75$0.10
Output $/Mtok$3.75$0.40
Coding index48.38.9
Independent measurements behind it11
Cost per solved task$1.49Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.6 Flash better than GPT-4.1 Nano for coding?

Pick Gemini 3.6 Flash for coding: it scores 48.3 on the Vibe Coding Index against 8.9 for GPT-4.1 Nano. Pick GPT-4.1 Nano when output tokens cost 9.4x less.

Which is cheaper, Gemini 3.6 Flash or GPT-4.1 Nano?

Gemini 3.6 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; GPT-4.1 Nano costs $0.10 and $0.40. Cost per solved task is known for Gemini 3.6 Flash only.

Which has the bigger context window, Gemini 3.6 Flash or GPT-4.1 Nano?

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

How many benchmarks is the Gemini 3.6 Flash vs GPT-4.1 Nano comparison based on?

55 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-4.1 Nano's on 1. Where only one model has a result, the page says so instead of naming a winner.

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