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Gemini 2.5 Pro vs GPT-4.1 Nano

Gemini 2.5 Pro leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 16.1 to 7.8, and GPT-4.1 Nano costs 25.0x less per output token ($0.40 vs $10.00 per million). Updated October 22, 2026; 55 benchmarks have a result for both.

Replace Gemini 2.5 Pro Replace GPT-4.1 Nano
Gemini 2.5 ProGoogle
Coding
19.1
Overall
41.8
Output $/M
$10.00
55
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
vs boards won of 55 shared

Gemini 2.5 Pro or GPT-4.1 Nano: which to pick

Only Gemini 2.5 Pro has a coding score, 19.1 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding.

Pick GPT-4.1 Nano for output tokens 25.0x cheaper ($0.40 vs $10.00 per million).

Model AGemini 2.5 ProGoogle19.1/1003 independent benchmarks$0.64 per solved taskModel BGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
55
Gemini 2.5 Pro only
35
GPT-4.1 Nano only
16
Like-for-like categories
8 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, GPT-4.1 Nano not benchmarked.
Widest category
Math, 48.5 points apart on average over 5 shared benchmarks.
Widest single gap
AA Math Index: Gemini 2.5 Pro 87.7 against GPT-4.1 Nano 24.0, 63.7 points apart on a 0 to 100 scale.
Output price
Gemini 2.5 Pro $10.00 against GPT-4.1 Nano $0.40 per million output tokens, 25.0x apart.
Context window
Gemini 2.5 Pro 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 2.5 ProBarsGPT-4.1 NanoTies
Coding60
Intelligence20
Agentic work10
Reasoning90
Math50
Knowledge70
Web design60
General190
All shared boards550
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
Coding benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-4.1 NanoLeader
Aider polyglotNot measured8.9%Only GPT-4.1 Nano measured
SWE-bench Verified53.6%Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev1226Not measuredOnly Gemini 2.5 Pro measured
AA Coding Index33.311.1Gemini 2.5 Pro
LiveCodeBench (Vals AI)Not measured42.7%Only GPT-4.1 Nano measured
SWE-bench Verified (Vals AI)54.4%Not measuredOnly Gemini 2.5 Pro measured
Vibe Code Bench (Vals AI)0.4%Not measuredOnly Gemini 2.5 Pro measured
LiveCodeBench (Artificial Analysis run)80.1%32.6%Gemini 2.5 Pro
SciCode46.3%Not measuredOnly Gemini 2.5 Pro measured
Terminal-Bench Hard (Artificial Analysis run)26.5%3.8%Gemini 2.5 Pro
Terminal-Bench32.6%Not measuredOnly Gemini 2.5 Pro measured
GSO-Bench3.9%Not measuredOnly Gemini 2.5 Pro measured
WeirdML54.0%19.0%Gemini 2.5 Pro
LMArena Text: coding14521306Gemini 2.5 Pro
LMArena Text: software and IT14591305Gemini 2.5 Pro
LMArena WebDev: HTML1235Not measuredOnly Gemini 2.5 Pro measured
LMArena WebDev: from an image1285Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-4.1 NanoLeader
AA Intelligence Index16.17.8Gemini 2.5 Pro
Epoch Capabilities Index145.1129.5Gemini 2.5 Pro
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-4.1 NanoLeader
AA Agentic Index1.6Not measuredOnly Gemini 2.5 Pro measured
τ²-Bench Telecom54.1%17.3%Gemini 2.5 Pro
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
Berkeley Function Calling Leaderboard (BFCL)Not measured33.1%Only GPT-4.1 Nano measured
BrowseComp-Plus29.5%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index90
Reasoning benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-4.1 NanoLeader
GPQA DiamondNot measured50.8%Only GPT-4.1 Nano measured
MMMU Pro (Vals AI)Not measured55.0%Only GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)84.4%51.2%Gemini 2.5 Pro
Humanity's Last Exam (Artificial Analysis run)22.5%3.8%Gemini 2.5 Pro
GPQA Diamond (Epoch AI run)85.3%48.9%Gemini 2.5 Pro
ARC-AGI41.0%0.0%Gemini 2.5 Pro
ARC-AGI-24.9%0.0%Gemini 2.5 Pro
Chess puzzlesNot measured0.0%Only GPT-4.1 Nano measured
LMArena Text: hard prompts14551286Gemini 2.5 Pro
LMArena Text: expert14521271Gemini 2.5 Pro
LMArena Text: hard prompts in English14531293Gemini 2.5 Pro
LMArena Vision: diagrams1274Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: homework1281Not measuredOnly Gemini 2.5 Pro measured
Kagi LLM Benchmark70.3%33.3%Gemini 2.5 Pro
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index50
Math benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-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 Index87.724.0Gemini 2.5 Pro
AIME 2025 (Artificial Analysis run)87.7%24.0%Gemini 2.5 Pro
OTIS Mock AIME84.7%28.9%Gemini 2.5 Pro
FrontierMath, tiers 1 to 324.6%Not measuredOnly Gemini 2.5 Pro measured
FrontierMath, tier 40.0%Not measuredOnly Gemini 2.5 Pro measured
MATH level 5Not measured70.0%Only GPT-4.1 Nano measured
LMArena Text: math14501274Gemini 2.5 Pro
LMArena Text: mathematical work14541274Gemini 2.5 Pro
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index70
Knowledge benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-4.1 NanoLeader
MMLU ProNot measured63.5%Only GPT-4.1 Nano measured
LegalBench (Vals AI)Not measured61.1%Only GPT-4.1 Nano measured
CaseLaw (Vals AI)63.9%Not measuredOnly Gemini 2.5 Pro measured
CorpFin (Vals AI)60.8%42.1%Gemini 2.5 Pro
TaxEval (Vals AI)Not measured60.8%Only GPT-4.1 Nano measured
MortgageTax (Vals AI)68.9%52.8%Gemini 2.5 Pro
MedQA (Vals AI)Not measured68.2%Only GPT-4.1 Nano measured
MedCode (Vals AI)50.6%Not measuredOnly Gemini 2.5 Pro measured
MMLU Pro (Artificial Analysis run)86.2%65.7%Gemini 2.5 Pro
SimpleQA VerifiedNot measured6.0%Only GPT-4.1 Nano measured
LMArena Text: science14801297Gemini 2.5 Pro
LMArena Text: medicine and healthcare14761276Gemini 2.5 Pro
LMArena Text: legal and government14801300Gemini 2.5 Pro
LMArena Text: business and finance14391267Gemini 2.5 Pro
FACTS Benchmark Suite61.5%Not measuredOnly Gemini 2.5 Pro measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index60
Web design benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-4.1 NanoLeader
Design Arena: websites1167972Gemini 2.5 Pro
Design Arena: UI components1137913Gemini 2.5 Pro
Design Arena: game dev1111970Gemini 2.5 Pro
Design Arena: data viz1222891Gemini 2.5 Pro
Design Arena: 3D1080924Gemini 2.5 Pro
Design Arena: all code categories1152962Gemini 2.5 Pro
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for Gemini 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-4.1 NanoLeader
SAGE (Vals AI)41.9%Not measuredOnly Gemini 2.5 Pro measured
MedScribe (Vals AI)73.5%Not measuredOnly Gemini 2.5 Pro measured
IFBench48.7%32.0%Gemini 2.5 Pro
Long context reasoning (AA-LCR)69.0%20.3%Gemini 2.5 Pro
DTBench82.4%52.5%Gemini 2.5 Pro
LMCA34.8%5.5%Gemini 2.5 Pro
Fiction.LiveBenchNot measured25.0%Only GPT-4.1 Nano measured
Creative writing (Lech Mazur)83.8%Not measuredOnly Gemini 2.5 Pro measured
LMArena Text14581285Gemini 2.5 Pro
LMArena Text: instruction following14371266Gemini 2.5 Pro
LMArena Text: creative writing14541260Gemini 2.5 Pro
LMArena Vision12631063Gemini 2.5 Pro
LMArena Text: English14581303Gemini 2.5 Pro
LMArena Text: non-English14521260Gemini 2.5 Pro
LMArena Text: Chinese15071270Gemini 2.5 Pro
LMArena Text: German14871288Gemini 2.5 Pro
LMArena Text: Japanese14611198Gemini 2.5 Pro
LMArena Text: Korean1434Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: French1473Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: Spanish1474Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: Russian14611261Gemini 2.5 Pro
LMArena Text: Polish1479Not measuredOnly Gemini 2.5 Pro measured
LMArena Text: multi-turn14531277Gemini 2.5 Pro
LMArena Text: longer queries14491283Gemini 2.5 Pro
LMArena Text: writing and language14541261Gemini 2.5 Pro
LMArena Text: entertainment and media14411243Gemini 2.5 Pro
LMArena Vision: English12611101Gemini 2.5 Pro
LMArena Vision: Chinese1300Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: reading text1270Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: humor1262Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: captioning1304Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: recognizing things1283Not measuredOnly Gemini 2.5 Pro measured
LMArena Vision: creative writing1265Not measuredOnly Gemini 2.5 Pro measured
LMArena Document1421Not measuredOnly Gemini 2.5 Pro 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 2.5 Pro and GPT-4.1 Nano
BenchmarkGemini 2.5 ProGPT-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 2.5 Pro$0.0063Fits 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 2.5 Pro$0.092Fits 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 2.5 Pro$0.350Fits 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 2.5 Pro and GPT-4.1 Nano
SpecificationGoogle Gemini 2.5 ProOpenAI GPT-4.1 Nano
MakerGoogleOpenAI
WeightsNo public weights listedNo public weights listed
ReleasedJune 17, 2025April 14, 2025
Context window1.05M1.05M
Input $/Mtok$1.25$0.10
Output $/Mtok$10.00$0.40
Coding index19.1Not benchmarked
Independent measurements behind it30
Cost per solved task$0.64Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 2.5 Pro better than GPT-4.1 Nano for coding?

Only Gemini 2.5 Pro has a coding score, 19.1 on the Vibe Coding Index; GPT-4.1 Nano has none, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 25.0x cheaper ($0.40 vs $10.00 per million).

Which is cheaper, Gemini 2.5 Pro or GPT-4.1 Nano?

Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; GPT-4.1 Nano costs $0.10 and $0.40. Cost per solved task is known for Gemini 2.5 Pro only.

Which has the bigger context window, Gemini 2.5 Pro or GPT-4.1 Nano?

Gemini 2.5 Pro, with 1.05M tokens against 1.05M.

How many benchmarks is the Gemini 2.5 Pro vs GPT-4.1 Nano comparison based on?

55 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 GPT-4.1 Nano's on 0. Where only one model has a result, the page says so instead of naming a winner.

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