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Gemma 3 27B vs GPT-5.4

GPT-5.4 leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 39.0 to 4.9, and Gemma 3 27B costs 50.0x less per output token ($0.30 vs $15.00 per million). Updated October 22, 2026; 51 benchmarks have a result for both.

Gemma 3 27BGoogle
Coding
No data
Overall
31.4
Output $/M
$0.30
0
GPT-5.4OpenAI
Coding
64.4
Overall
69.6
Output $/M
$15.00
51
vs boards won of 51 shared

Gemma 3 27B or GPT-5.4: which to pick

Only GPT-5.4 has a coding score, 64.4 on the Vibe Coding Index; Gemma 3 27B has none, so the two cannot be ranked on coding.

Pick Gemma 3 27B for output tokens 50.0x cheaper ($0.30 vs $15.00 per million).

Shared results
51
Gemma 3 27B only
15
GPT-5.4 only
59
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-5.4 64.4 from 3 benchmarks.
Widest category
Agentic work, 76.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Gemma 3 27B 10.5% against GPT-5.4 87.1%, 76.6 points apart on a 0 to 100 scale.
Output price
Gemma 3 27B $0.30 against GPT-5.4 $15.00 per million output tokens, 50.0x apart.
Context window
Gemma 3 27B takes 131K tokens, GPT-5.4 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 27BBarsGPT-5.4Ties
Coding04
Intelligence02
Agentic work01
Reasoning09
Math03
Knowledge04
General028
All shared boards051
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
Aider polyglot4.9%Not measuredOnly Gemma 3 27B measured
LMArena WebDevNot measured1464Only GPT-5.4 measured
AA Coding Index10.171.1GPT-5.4
LiveCodeBench (Vals AI)Not measured84.1%Only GPT-5.4 measured
SWE-bench Verified (Vals AI)Not measured78.2%Only GPT-5.4 measured
Vibe Code Bench (Vals AI)Not measured67.4%Only GPT-5.4 measured
Code migration (Vals AI)Not measured35.0%Only GPT-5.4 measured
ProgramBench (Vals AI)Not measured0.5%Only GPT-5.4 measured
SkillsBench (Vals AI)Not measured51.7%Only GPT-5.4 measured
LiveCodeBench (Artificial Analysis run)13.7%Not measuredOnly Gemma 3 27B measured
SciCode23.3%Not measuredOnly Gemma 3 27B measured
Terminal-Bench Hard (Artificial Analysis run)3.8%57.6%GPT-5.4
Terminal-BenchNot measured81.8%Only GPT-5.4 measured
GSO-BenchNot measured31.4%Only GPT-5.4 measured
WeirdMLNot measured77.7%Only GPT-5.4 measured
MirrorCodeNot measured15.6%Only GPT-5.4 measured
ALE-BenchNot measured1607.0Only GPT-5.4 measured
LMArena Text: coding13221496GPT-5.4
LMArena Text: software and IT13541491GPT-5.4
LMArena WebDev: ReactNot measured1454Only GPT-5.4 measured
LMArena WebDev: HTMLNot measured1478Only GPT-5.4 measured
LMArena WebDev: from an imageNot measured1436Only GPT-5.4 measured
SciCode0.0%Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 16 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
AA Intelligence Index4.939.0GPT-5.4
Epoch Capabilities Index130.0157.3GPT-5.4
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
AA Agentic Index0.1Not measuredOnly Gemma 3 27B measured
Design Arena: agents building web appsNot measured1059Only GPT-5.4 measured
Design Arena: agents building full-stack appsNot measured1017Only GPT-5.4 measured
Design Arena: agents building mobile appsNot measured1087Only GPT-5.4 measured
Design Arena: agents building Android appsNot measured1031Only GPT-5.4 measured
Design Arena: agents building Godot gamesNot measured1135Only GPT-5.4 measured
τ²-Bench Telecom10.5%87.1%GPT-5.4
APEX-AgentsNot measured52.4%Only GPT-5.4 measured
METR time horizonsNot measured74.3%Only GPT-5.4 measured
DeepResearch BenchNot measured35.1%Only GPT-5.4 measured
PostTrainBenchNot measured19.0%Only GPT-5.4 measured
Vending-Bench 2Not measured$6,144Only GPT-5.4 measured
Berkeley Function Calling Leaderboard (BFCL)29.5%Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
GPQA DiamondNot measured91.7%Only GPT-5.4 measured
MMMU Pro (Vals AI)Not measured87.5%Only GPT-5.4 measured
GPQA Diamond (Artificial Analysis run)42.8%92.0%GPT-5.4
Humanity's Last Exam (Artificial Analysis run)4.4%43.7%GPT-5.4
GPQA Diamond (Epoch AI run)47.7%93.3%GPT-5.4
ARC-AGINot measured93.7%Only GPT-5.4 measured
ARC-AGI-2Not measured74.0%Only GPT-5.4 measured
Chess puzzlesNot measured48.0%Only GPT-5.4 measured
Mystery game puzzlesNot measured37.0%Only GPT-5.4 measured
EBR-benchNot measured25.4%Only GPT-5.4 measured
LMArena Text: hard prompts13401485GPT-5.4
LMArena Text: expert13041507GPT-5.4
LMArena Text: hard prompts in English13531479GPT-5.4
LMArena Vision: diagrams11561327GPT-5.4
LMArena Vision: homework11601336GPT-5.4
Kagi LLM Benchmark35.1%63.8%GPT-5.4
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
AIMENot measured96.7%Only GPT-5.4 measured
AA Math Index20.7Not measuredOnly Gemma 3 27B measured
AIME 2025 (Artificial Analysis run)20.7%Not measuredOnly Gemma 3 27B measured
OTIS Mock AIME22.5%97.8%GPT-5.4
FrontierMath, tiers 1 to 3Not measured78.6%Only GPT-5.4 measured
FrontierMath, tier 4Not measured49.0%Only GPT-5.4 measured
ProofBenchNot measured56.0%Only GPT-5.4 measured
MATH level 574.0%Not measuredOnly Gemma 3 27B measured
LMArena Text: math13121488GPT-5.4
LMArena Text: mathematical work13271497GPT-5.4
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
MMLU ProNot measured87.5%Only GPT-5.4 measured
LegalBench (Vals AI)Not measured86.0%Only GPT-5.4 measured
CaseLaw (Vals AI)Not measured63.8%Only GPT-5.4 measured
CorpFin (Vals AI)Not measured65.3%Only GPT-5.4 measured
TaxEval (Vals AI)Not measured74.0%Only GPT-5.4 measured
MortgageTax (Vals AI)Not measured68.3%Only GPT-5.4 measured
MedQA (Vals AI)Not measured96.1%Only GPT-5.4 measured
MedCode (Vals AI)Not measured41.3%Only GPT-5.4 measured
MMLU Pro (Artificial Analysis run)66.9%Not measuredOnly Gemma 3 27B measured
SimpleQA VerifiedNot measured45.1%Only GPT-5.4 measured
GeoBench52.0%Not measuredOnly Gemma 3 27B measured
LMArena Text: science13831479GPT-5.4
LMArena Text: medicine and healthcare13911458GPT-5.4
LMArena Text: legal and government13751486GPT-5.4
LMArena Text: business and finance13601474GPT-5.4
FACTS Benchmark Suite29.1%Not measuredOnly Gemma 3 27B measured
Neither model has a result on the other 2 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
Design Arena: websitesNot measured1198Only GPT-5.4 measured
Design Arena: UI componentsNot measured1212Only GPT-5.4 measured
Design Arena: game devNot measured1194Only GPT-5.4 measured
Design Arena: data vizNot measured1196Only GPT-5.4 measured
Design Arena: 3DNot measured1065Only GPT-5.4 measured
Design Arena: all code categoriesNot measured1179Only GPT-5.4 measured
Design Arena: SVGNot measured1141Only GPT-5.4 measured
Design Arena: ASCII artNot measured1188Only GPT-5.4 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index028
General benchmarks for Gemma 3 27B and GPT-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
SAGE (Vals AI)Not measured43.3%Only GPT-5.4 measured
MedScribe (Vals AI)Not measured77.5%Only GPT-5.4 measured
IFBench31.8%73.9%GPT-5.4
Long context reasoning (AA-LCR)7.3%82.0%GPT-5.4
DTBench52.5%94.4%GPT-5.4
LMCA12.3%52.0%GPT-5.4
Fiction.LiveBench33.3%Not measuredOnly Gemma 3 27B measured
Creative writing (Lech Mazur)79.9%Not measuredOnly Gemma 3 27B measured
CL-benchNot measured27.9%Only GPT-5.4 measured
Furniture assemblyNot measured37.5%Only GPT-5.4 measured
CL-bench LifeNot measured21.7%Only GPT-5.4 measured
LMArena Text13581469GPT-5.4
LMArena Text: instruction following13211469GPT-5.4
LMArena Text: creative writing13451439GPT-5.4
LMArena Vision11651303GPT-5.4
LMArena Text: English13771467GPT-5.4
LMArena Text: non-English13341465GPT-5.4
LMArena Text: Chinese13461520GPT-5.4
LMArena Text: German13621472GPT-5.4
LMArena Text: Japanese12871485GPT-5.4
LMArena Text: Korean13081449GPT-5.4
LMArena Text: French13681493GPT-5.4
LMArena Text: Spanish13491452GPT-5.4
LMArena Text: Russian13491480GPT-5.4
LMArena Text: Polish13451472GPT-5.4
LMArena Text: multi-turn13451482GPT-5.4
LMArena Text: longer queries13331473GPT-5.4
LMArena Text: writing and language13471458GPT-5.4
LMArena Text: entertainment and media13201438GPT-5.4
LMArena Vision: English11881301GPT-5.4
LMArena Vision: Chinese11641354GPT-5.4
LMArena Vision: reading text11561312GPT-5.4
LMArena Vision: humor11661284GPT-5.4
LMArena Vision: captioning1151Not measuredOnly Gemma 3 27B measured
LMArena Vision: recognizing things11961251GPT-5.4
LMArena Vision: creative writing11771283GPT-5.4
LMArena DocumentNot measured1471Only GPT-5.4 measured
Neither model has a result on the other 9 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-5.4
BenchmarkGemma 3 27BGPT-5.4Leader
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-5.4$0.010Fits in one request

Gemma 3 27B costs less

Repository review

50K input + 3K output tokens

Gemma 3 27B$0.0049Fits in one request
GPT-5.4$0.170Fits in one request

Gemma 3 27B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 27B$0.019Exceeds the context window
GPT-5.4$0.650Fits in one request

Gemma 3 27B 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-5.4
SpecificationGoogle Gemma 3 27BOpenAI GPT-5.4
MakerGoogleOpenAI
WeightsOpen weightsNo public weights listed
ReleasedMarch 12, 2025March 5, 2026
Context window131K1.05M
Input $/Mtok$0.08$2.50
Output $/Mtok$0.30$15.00
Coding indexNot benchmarked64.4
Independent measurements behind it03
Cost per solved taskNot computable$1.02
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 27B better than GPT-5.4 for coding?

Only GPT-5.4 has a coding score, 64.4 on the Vibe Coding Index; Gemma 3 27B has none, so the two cannot be ranked on coding. Pick Gemma 3 27B for output tokens 50.0x cheaper ($0.30 vs $15.00 per million).

Which is cheaper, Gemma 3 27B or GPT-5.4?

Gemma 3 27B costs $0.08 per million input tokens and $0.30 per million output tokens; GPT-5.4 costs $2.50 and $15.00. Cost per solved task is known for GPT-5.4 only.

Which has the bigger context window, Gemma 3 27B or GPT-5.4?

GPT-5.4, with 1.05M tokens against 131K.

How many benchmarks is the Gemma 3 27B vs GPT-5.4 comparison based on?

51 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-5.4's on 3. Where only one model has a result, the page says so instead of naming a winner.

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