Enter opens the highlighted result. Esc closes.

Gemma 3 27B vs GPT-5 Nano

GPT-5 Nano leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 13.0 to 4.9, and Gemma 3 27B costs 1.3x less per output token ($0.30 vs $0.40 per million). Updated October 22, 2026; 54 benchmarks have a result for both.

Replace Gemma 3 27B Replace GPT-5 Nano
Gemma 3 27BGoogle
Coding
No data
Overall
31.4
Output $/M
$0.30
29
GPT-5 NanoOpenAI
Coding
No data
Overall
35.6
Output $/M
$0.40
25
vs boards won of 54 shared

Gemma 3 27B or GPT-5 Nano: which to pick

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

Pick Gemma 3 27B for output tokens 1.3x cheaper ($0.30 vs $0.40 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Model AGemma 3 27BGoogleNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-5 NanoOpenAINot benchmarkedNo coding benchmark$0.109 per solved task
Shared results
54
Gemma 3 27B only
12
GPT-5 Nano only
33
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 27B not benchmarked, GPT-5 Nano not benchmarked.
Widest category
Math, 34.5 points apart on average over 6 shared benchmarks.
Widest single gap
LiveCodeBench (Artificial Analysis run): Gemma 3 27B 13.7% against GPT-5 Nano 78.9%, 65.2 points apart on a 0 to 100 scale.
Output price
Gemma 3 27B $0.30 against GPT-5 Nano $0.40 per million output tokens, 1.3x apart.
Context window
Gemma 3 27B takes 131K tokens, GPT-5 Nano 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
CategoryGemma 3 27BBarsGPT-5 NanoTies
Coding13
Intelligence02
Agentic work02
Reasoning45
Math15
Knowledge41
General197
All shared boards2925
CodingLike-for-likeSix of these boards feed the Vibe Coding Index13
Coding benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
Aider polyglot4.9%Not measuredOnly Gemma 3 27B measured
SWE-bench VerifiedNot measured34.8%Only GPT-5 Nano measured
AA Coding Index10.1Not measuredOnly Gemma 3 27B measured
LiveCodeBench (Vals AI)Not measured70.2%Only GPT-5 Nano measured
LiveCodeBench (Artificial Analysis run)13.7%78.9%GPT-5 Nano
SciCode23.3%Not measuredOnly Gemma 3 27B measured
Terminal-Bench Hard (Artificial Analysis run)3.8%17.4%GPT-5 Nano
Terminal-BenchNot measured21.8%Only GPT-5 Nano measured
WeirdMLNot measured38.1%Only GPT-5 Nano measured
LMArena Text: coding13221351GPT-5 Nano
LMArena Text: software and IT13541345Gemma 3 27B
SciCode0.0%Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
AA Intelligence Index4.913.0GPT-5 Nano
Epoch Capabilities Index130.0139.2GPT-5 Nano
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
AA Agentic Index0.1Not measuredOnly Gemma 3 27B measured
τ²-Bench Telecom10.5%36.5%GPT-5 Nano
Berkeley Function Calling Leaderboard (BFCL)29.5%51.4%GPT-5 Nano
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index45
Reasoning benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
GPQA DiamondNot measured63.4%Only GPT-5 Nano measured
MMMU Pro (Vals AI)Not measured70.9%Only GPT-5 Nano measured
GPQA Diamond (Artificial Analysis run)42.8%67.6%GPT-5 Nano
Humanity's Last Exam (Artificial Analysis run)4.4%9.5%GPT-5 Nano
GPQA Diamond (Epoch AI run)47.7%69.4%GPT-5 Nano
ARC-AGINot measured20.7%Only GPT-5 Nano measured
ARC-AGI-2Not measured2.6%Only GPT-5 Nano measured
Chess puzzlesNot measured22.0%Only GPT-5 Nano measured
Mystery game puzzlesNot measured9.0%Only GPT-5 Nano measured
VPCTNot measured37.2%Only GPT-5 Nano measured
LMArena Text: hard prompts13401328Gemma 3 27B
LMArena Text: expert13041321GPT-5 Nano
LMArena Text: hard prompts in English13531338Gemma 3 27B
LMArena Vision: diagrams11561141Gemma 3 27B
LMArena Vision: homework11601157Gemma 3 27B
Kagi LLM Benchmark35.1%62.2%GPT-5 Nano
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index15
Math benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
AIMENot measured81.2%Only GPT-5 Nano measured
MATH 500 (Vals AI)Not measured93.8%Only GPT-5 Nano measured
MGSM (Vals AI)Not measured89.3%Only GPT-5 Nano measured
AA Math Index20.783.7GPT-5 Nano
AIME 2025 (Artificial Analysis run)20.7%83.7%GPT-5 Nano
OTIS Mock AIME22.5%81.1%GPT-5 Nano
FrontierMath, tiers 1 to 3Not measured20.0%Only GPT-5 Nano measured
FrontierMath, tier 4Not measured2.4%Only GPT-5 Nano measured
ProofBenchNot measured12.0%Only GPT-5 Nano measured
MATH level 574.0%95.2%GPT-5 Nano
LMArena Text: math13121317GPT-5 Nano
LMArena Text: mathematical work13271326Gemma 3 27B
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index41
Knowledge benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
MMLU ProNot measured76.1%Only GPT-5 Nano measured
LegalBench (Vals AI)Not measured50.1%Only GPT-5 Nano measured
CaseLaw (Vals AI)Not measured52.6%Only GPT-5 Nano measured
TaxEval (Vals AI)Not measured67.4%Only GPT-5 Nano measured
MortgageTax (Vals AI)Not measured53.6%Only GPT-5 Nano measured
MedQA (Vals AI)Not measured93.3%Only GPT-5 Nano measured
MedCode (Vals AI)Not measured30.4%Only GPT-5 Nano measured
MMLU Pro (Artificial Analysis run)66.9%78.0%GPT-5 Nano
SimpleQA VerifiedNot measured11.7%Only GPT-5 Nano measured
GeoBench52.0%Not measuredOnly Gemma 3 27B measured
LMArena Text: science13831318Gemma 3 27B
LMArena Text: medicine and healthcare13911335Gemma 3 27B
LMArena Text: legal and government13751298Gemma 3 27B
LMArena Text: business and finance13601311Gemma 3 27B
FACTS Benchmark Suite29.1%Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
Design Arena: websitesNot measured1101Only GPT-5 Nano measured
Design Arena: UI componentsNot measured1064Only GPT-5 Nano measured
Design Arena: game devNot measured1044Only GPT-5 Nano measured
Design Arena: data vizNot measured1056Only GPT-5 Nano measured
Design Arena: 3DNot measured965Only GPT-5 Nano measured
Design Arena: all code categoriesNot measured1084Only GPT-5 Nano measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index197
General benchmarks for Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 NanoLeader
SAGE (Vals AI)Not measured30.4%Only GPT-5 Nano measured
MedScribe (Vals AI)Not measured72.9%Only GPT-5 Nano measured
IFBench31.8%67.6%GPT-5 Nano
Long context reasoning (AA-LCR)7.3%45.0%GPT-5 Nano
DTBench52.5%62.7%GPT-5 Nano
LMCA12.3%7.9%Gemma 3 27B
Fiction.LiveBench33.3%44.4%GPT-5 Nano
Creative writing (Lech Mazur)79.9%Not measuredOnly Gemma 3 27B measured
LMArena Text13581320Gemma 3 27B
LMArena Text: instruction following13211306Gemma 3 27B
LMArena Text: creative writing13451249Gemma 3 27B
LMArena Vision11651159Gemma 3 27B
LMArena Text: English13771321Gemma 3 27B
LMArena Text: non-English13341313Gemma 3 27B
LMArena Text: Chinese13461356GPT-5 Nano
LMArena Text: German13621327Gemma 3 27B
LMArena Text: Japanese12871227Gemma 3 27B
LMArena Text: Korean13081269Gemma 3 27B
LMArena Text: French1368Not measuredOnly Gemma 3 27B measured
LMArena Text: Spanish13491360GPT-5 Nano
LMArena Text: Russian13491296Gemma 3 27B
LMArena Text: Polish13451314Gemma 3 27B
LMArena Text: multi-turn13451311Gemma 3 27B
LMArena Text: longer queries13331312Gemma 3 27B
LMArena Text: writing and language13471283Gemma 3 27B
LMArena Text: entertainment and media13201268Gemma 3 27B
LMArena Vision: English11881170Gemma 3 27B
LMArena Vision: Chinese11641176GPT-5 Nano
LMArena Vision: reading text11561152Gemma 3 27B
LMArena Vision: humor11661110Gemma 3 27B
LMArena Vision: captioning1151Not measuredOnly Gemma 3 27B measured
LMArena Vision: recognizing things1196Not measuredOnly Gemma 3 27B measured
LMArena Vision: creative writing1177Not measuredOnly Gemma 3 27B 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 Gemma 3 27B and GPT-5 Nano
BenchmarkGemma 3 27BGPT-5 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 27B$0.0002Fits in one request
GPT-5 Nano$0.0003Fits in one request

Gemma 3 27B costs less

Repository review

50K input + 3K output tokens

Gemma 3 27B$0.0049Fits in one request
GPT-5 Nano$0.0037Fits in one request

GPT-5 Nano costs less

Agent loop

200K input + 10K output tokens

Gemma 3 27B$0.019Exceeds the context window
GPT-5 Nano$0.014Fits in one request

GPT-5 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 Gemma 3 27B and GPT-5 Nano
SpecificationGoogle Gemma 3 27BOpenAI GPT-5 Nano
MakerGoogleOpenAI
WeightsOpen weightsNo public weights listed
ReleasedMarch 12, 2025August 7, 2025
Context window131K400K
Input $/Mtok$0.08$0.05
Output $/Mtok$0.30$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computable$0.109
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 27B better than GPT-5 Nano for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 27B for output tokens 1.3x cheaper ($0.30 vs $0.40 per million) and work measured by LiveCodeBench (Artificial Analysis run) or Terminal-Bench Hard (Artificial Analysis run), where it leads.

Which is cheaper, Gemma 3 27B or GPT-5 Nano?

Gemma 3 27B costs $0.08 per million input tokens and $0.30 per million output tokens; GPT-5 Nano costs $0.05 and $0.40. Cost per solved task is known for GPT-5 Nano only.

Which has the bigger context window, Gemma 3 27B or GPT-5 Nano?

GPT-5 Nano, with 400K tokens against 131K.

How many benchmarks is the Gemma 3 27B vs GPT-5 Nano comparison based on?

54 benchmarks have a result for both models as of October 22, 2026. Gemma 3 27B's coding index rests on 0 independent benchmarks and GPT-5 Nano's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next