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Gemma 3 12B vs GPT-4.1 Nano

GPT-4.1 Nano leads Gemma 3 12B on the Artificial Analysis Intelligence Index, 7.8 to 3.8, and Gemma 3 12B costs 2.5x less per output token ($0.1625 vs $0.40 per million). Updated October 22, 2026; 40 benchmarks have a result for both.

Replace Gemma 3 12B Replace GPT-4.1 Nano
Gemma 3 12BGoogle
Coding
No data
Overall
28.0
Output $/M
$0.1625
22
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
18
vs boards won of 40 shared

Gemma 3 12B or GPT-4.1 Nano: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick Gemma 3 12B for output tokens 2.5x cheaper ($0.1625 vs $0.40 per million) and work measured by AA Coding Index or LiveCodeBench (Artificial Analysis run), where it leads.

Model AGemma 3 12BGoogleNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
40
Gemma 3 12B only
3
GPT-4.1 Nano only
31
Like-for-like categories
7 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
Gemma 3 12B not benchmarked, GPT-4.1 Nano not benchmarked.
Widest category
Knowledge, 11.8 points apart on average over 5 shared benchmarks.
Widest single gap
LiveCodeBench (Artificial Analysis run): Gemma 3 12B 13.7% against GPT-4.1 Nano 32.6%, 18.9 points apart on a 0 to 100 scale.
Output price
Gemma 3 12B $0.1625 against GPT-4.1 Nano $0.40 per million output tokens, 2.5x apart.
Context window
Gemma 3 12B takes 131K 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
CategoryGemma 3 12BBarsGPT-4.1 NanoTies
Coding14
Intelligence02
Agentic work02
Reasoning33
Math23
Knowledge41
General123
All shared boards2218
CodingLike-for-likeSix of these boards feed the Vibe Coding Index14
Coding benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-4.1 NanoLeader
Aider polyglotNot measured8.9%Only GPT-4.1 Nano measured
AA Coding Index5.811.1GPT-4.1 Nano
LiveCodeBench (Vals AI)Not measured42.7%Only GPT-4.1 Nano measured
LiveCodeBench (Artificial Analysis run)13.7%32.6%GPT-4.1 Nano
SciCode16.4%Not measuredOnly Gemma 3 12B measured
Terminal-Bench Hard (Artificial Analysis run)0.8%3.8%GPT-4.1 Nano
WeirdMLNot measured19.0%Only GPT-4.1 Nano measured
LMArena Text: coding12811306GPT-4.1 Nano
LMArena Text: software and IT13131305Gemma 3 12B
SciCode0.0%Not measuredOnly Gemma 3 12B measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-4.1 NanoLeader
AA Intelligence Index3.87.8GPT-4.1 Nano
Epoch Capabilities Index123.5129.5GPT-4.1 Nano
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-4.1 NanoLeader
AA Agentic Index0.1Not measuredOnly Gemma 3 12B measured
τ²-Bench Telecom10.8%17.3%GPT-4.1 Nano
Berkeley Function Calling Leaderboard (BFCL)30.4%33.1%GPT-4.1 Nano
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
Reasoning benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-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)34.9%51.2%GPT-4.1 Nano
Humanity's Last Exam (Artificial Analysis run)4.2%3.8%Gemma 3 12B
GPQA Diamond (Epoch AI run)39.5%48.9%GPT-4.1 Nano
ARC-AGINot measured0.0%Only GPT-4.1 Nano measured
ARC-AGI-2Not measured0.0%Only GPT-4.1 Nano measured
Chess puzzlesNot measured0.0%Only GPT-4.1 Nano measured
LMArena Text: hard prompts13091286Gemma 3 12B
LMArena Text: expert12481271GPT-4.1 Nano
LMArena Text: hard prompts in English13181293Gemma 3 12B
Kagi LLM BenchmarkNot measured33.3%Only GPT-4.1 Nano measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index23
Math benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-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 Index18.324.0GPT-4.1 Nano
AIME 2025 (Artificial Analysis run)18.3%24.0%GPT-4.1 Nano
OTIS Mock AIME16.7%28.9%GPT-4.1 Nano
MATH level 5Not measured70.0%Only GPT-4.1 Nano measured
LMArena Text: math13071274Gemma 3 12B
LMArena Text: mathematical work13361274Gemma 3 12B
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-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
CorpFin (Vals AI)Not measured42.1%Only GPT-4.1 Nano measured
TaxEval (Vals AI)Not measured60.8%Only GPT-4.1 Nano measured
MortgageTax (Vals AI)Not measured52.8%Only GPT-4.1 Nano measured
MedQA (Vals AI)Not measured68.2%Only GPT-4.1 Nano measured
MMLU Pro (Artificial Analysis run)59.5%65.7%GPT-4.1 Nano
SimpleQA VerifiedNot measured6.0%Only GPT-4.1 Nano measured
LMArena Text: science13661297Gemma 3 12B
LMArena Text: medicine and healthcare13341276Gemma 3 12B
LMArena Text: legal and government13811300Gemma 3 12B
LMArena Text: business and finance13761267Gemma 3 12B
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-4.1 NanoLeader
Design Arena: websitesNot measured972Only GPT-4.1 Nano measured
Design Arena: UI componentsNot measured913Only GPT-4.1 Nano measured
Design Arena: game devNot measured970Only GPT-4.1 Nano measured
Design Arena: data vizNot measured891Only GPT-4.1 Nano measured
Design Arena: 3DNot measured924Only GPT-4.1 Nano measured
Design Arena: all code categoriesNot measured962Only GPT-4.1 Nano measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index123
General benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-4.1 NanoLeader
IFBench36.7%32.0%Gemma 3 12B
Long context reasoning (AA-LCR)8.3%20.3%GPT-4.1 Nano
DTBench48.8%52.5%GPT-4.1 Nano
LMCA4.5%5.5%GPT-4.1 Nano
Fiction.LiveBenchNot measured25.0%Only GPT-4.1 Nano measured
LMArena Text13341285Gemma 3 12B
LMArena Text: instruction following12991266Gemma 3 12B
LMArena Text: creative writing13311260Gemma 3 12B
LMArena VisionNot measured1063Only GPT-4.1 Nano measured
LMArena Text: English13491303Gemma 3 12B
LMArena Text: non-English13181260Gemma 3 12B
LMArena Text: ChineseNot measured1270Only GPT-4.1 Nano measured
LMArena Text: German13701288Gemma 3 12B
LMArena Text: JapaneseNot measured1198Only GPT-4.1 Nano measured
LMArena Text: Russian13351261Gemma 3 12B
LMArena Text: multi-turn13341277Gemma 3 12B
LMArena Text: longer queries13171283Gemma 3 12B
LMArena Text: writing and language13071261Gemma 3 12B
LMArena Text: entertainment and media12971243Gemma 3 12B
LMArena Vision: EnglishNot measured1101Only GPT-4.1 Nano measured
Neither model has a result on the other 26 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 3 12B and GPT-4.1 Nano
BenchmarkGemma 3 12BGPT-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

Gemma 3 12B$0.0002Fits in one request
GPT-4.1 Nano$0.0003Fits in one request

Gemma 3 12B costs less

Repository review

50K input + 3K output tokens

Gemma 3 12B$0.0042Fits in one request
GPT-4.1 Nano$0.0062Fits in one request

Gemma 3 12B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 12B$0.017Exceeds the context window
GPT-4.1 Nano$0.024Fits in one request

Gemma 3 12B 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 Gemma 3 12B and GPT-4.1 Nano
SpecificationGoogle Gemma 3 12BOpenAI GPT-4.1 Nano
MakerGoogleOpenAI
WeightsOpen weightsNo public weights listed
ReleasedMarch 13, 2025April 14, 2025
Context window131K1.05M
Input $/Mtok$0.075$0.10
Output $/Mtok$0.1625$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 12B better than GPT-4.1 Nano for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 12B for output tokens 2.5x cheaper ($0.1625 vs $0.40 per million) and work measured by AA Coding Index or LiveCodeBench (Artificial Analysis run), where it leads.

Which is cheaper, Gemma 3 12B or GPT-4.1 Nano?

Gemma 3 12B costs $0.075 per million input tokens and $0.1625 per million output tokens; GPT-4.1 Nano costs $0.10 and $0.40. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 3 12B or GPT-4.1 Nano?

GPT-4.1 Nano, with 1.05M tokens against 131K.

How many benchmarks is the Gemma 3 12B vs GPT-4.1 Nano comparison based on?

40 benchmarks have a result for both models as of October 22, 2026. Gemma 3 12B's coding index rests on 0 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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