Enter opens the highlighted result. Esc closes.

Gemma 3 27B vs o3

o3 leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 20.2 to 4.9, and Gemma 3 27B costs 26.7x less per output token ($0.30 vs $8.00 per million). Updated October 22, 2026; 63 benchmarks have a result for both.

Gemma 3 27BGoogle
Coding
No data
Overall
31.4
Output $/M
$0.30
0
o3OpenAI
Coding
No data
Overall
51.1
Output $/M
$8.00
63
vs boards won of 63 shared

Gemma 3 27B or o3: 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 26.7x cheaper ($0.30 vs $8.00 per million) and work measured by Aider polyglot or LiveCodeBench (Artificial Analysis run), where it leads.

Shared results
63
Gemma 3 27B only
3
o3 only
39
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, o3 not benchmarked.
Widest category
Agentic work, 51.9 points apart on average over 2 shared benchmarks.
Widest single gap
Aider polyglot: Gemma 3 27B 4.9% against o3 81.3%, 76.4 points apart on a 0 to 100 scale.
Output price
Gemma 3 27B $0.30 against o3 $8.00 per million output tokens, 26.7x apart.
Context window
Gemma 3 27B takes 131K tokens, o3 200K.

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 27BBarso3Ties
Coding06
Intelligence02
Agentic work02
Reasoning09
Math06
Knowledge07
General031
All shared boards063
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
Coding benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
Aider polyglot4.9%81.3%o3
SWE-bench VerifiedNot measured58.4%Only o3 measured
SWE-bench MultimodalNot measured36.0%Only o3 measured
AA Coding Index10.1Not measuredOnly Gemma 3 27B measured
LiveCodeBench (Vals AI)Not measured83.9%Only o3 measured
LiveCodeBench (Artificial Analysis run)13.7%80.8%o3
SciCode23.3%Not measuredOnly Gemma 3 27B measured
Terminal-Bench Hard (Artificial Analysis run)3.8%37.1%o3
GSO-BenchNot measured8.8%Only o3 measured
WeirdMLNot measured52.4%Only o3 measured
ALE-BenchNot measured933.5Only o3 measured
LMArena Text: coding13221407o3
LMArena Text: software and IT13541415o3
SciCode0.0%9.2%o3
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
AA Intelligence Index4.920.2o3
Epoch Capabilities Index130.0146.7o3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
AA Agentic Index0.1Not measuredOnly Gemma 3 27B measured
τ²-Bench Telecom10.5%80.7%o3
METR time horizonsNot measured65.4%Only o3 measured
GDPvalNot measured30.8%Only o3 measured
DeepResearch BenchNot measured45.2%Only o3 measured
OSWorldNot measured23.0%Only o3 measured
Berkeley Function Calling Leaderboard (BFCL)29.5%63.0%o3
BrowseComp-PlusNot measured65.9%Only o3 measured
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
GPQA DiamondNot measured84.1%Only o3 measured
MMMU Pro (Vals AI)Not measured80.4%Only o3 measured
GPQA Diamond (Artificial Analysis run)42.8%82.7%o3
Humanity's Last Exam (Artificial Analysis run)4.4%20.1%o3
GPQA Diamond (Epoch AI run)47.7%81.8%o3
ARC-AGINot measured60.8%Only o3 measured
ARC-AGI-2Not measured6.5%Only o3 measured
SimpleBenchNot measured53.1%Only o3 measured
Chess puzzlesNot measured37.0%Only o3 measured
Mystery game puzzlesNot measured29.0%Only o3 measured
VPCTNot measured52.0%Only o3 measured
LMArena Text: hard prompts13401402o3
LMArena Text: expert13041402o3
LMArena Text: hard prompts in English13531411o3
LMArena Vision: diagrams11561220o3
LMArena Vision: homework11601234o3
Kagi LLM Benchmark35.1%67.6%o3
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index06
Math benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
AIMENot measured85.3%Only o3 measured
MATH 500 (Vals AI)Not measured94.6%Only o3 measured
MGSM (Vals AI)Not measured91.8%Only o3 measured
AA Math Index20.788.3o3
AIME 2025 (Artificial Analysis run)20.7%88.3%o3
OTIS Mock AIME22.5%84.4%o3
FrontierMath, tiers 1 to 3Not measured33.3%Only o3 measured
MATH level 574.0%97.8%o3
LMArena Text: math13121426o3
LMArena Text: mathematical work13271423o3
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index07
Knowledge benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
MMLU ProNot measured85.6%Only o3 measured
LegalBench (Vals AI)Not measured83.8%Only o3 measured
CorpFin (Vals AI)Not measured59.7%Only o3 measured
TaxEval (Vals AI)Not measured74.6%Only o3 measured
MortgageTax (Vals AI)Not measured65.7%Only o3 measured
MedQA (Vals AI)Not measured96.1%Only o3 measured
MedCode (Vals AI)Not measured47.3%Only o3 measured
MMLU Pro (Artificial Analysis run)66.9%85.3%o3
SimpleQA VerifiedNot measured49.4%Only o3 measured
GeoBench52.0%74.0%o3
LMArena Text: science13831429o3
LMArena Text: medicine and healthcare13911448o3
LMArena Text: legal and government13751428o3
LMArena Text: business and finance13601393o3
FACTS Benchmark Suite29.1%44.4%o3
Neither model has a result on the other 3 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
Design Arena: websitesNot measured1036Only o3 measured
Design Arena: UI componentsNot measured1017Only o3 measured
Design Arena: game devNot measured1034Only o3 measured
Design Arena: data vizNot measured1200Only o3 measured
Design Arena: all code categoriesNot measured1020Only o3 measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index031
General benchmarks for Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
SAGE (Vals AI)Not measured41.8%Only o3 measured
MedScribe (Vals AI)Not measured76.7%Only o3 measured
IFBench31.8%71.4%o3
Long context reasoning (AA-LCR)7.3%74.7%o3
DTBench52.5%84.8%o3
LMCA12.3%39.7%o3
Fiction.LiveBench33.3%88.9%o3
Creative writing (Lech Mazur)79.9%83.9%o3
CL-benchNot measured17.8%Only o3 measured
LMArena Text13581410o3
LMArena Text: instruction following13211368o3
LMArena Text: creative writing13451359o3
LMArena Vision11651214o3
LMArena Text: English13771417o3
LMArena Text: non-English13341401o3
LMArena Text: Chinese13461437o3
LMArena Text: German13621420o3
LMArena Text: Japanese12871403o3
LMArena Text: Korean13081370o3
LMArena Text: French13681430o3
LMArena Text: Spanish13491395o3
LMArena Text: Russian13491406o3
LMArena Text: Polish13451438o3
LMArena Text: multi-turn13451405o3
LMArena Text: longer queries13331372o3
LMArena Text: writing and language13471372o3
LMArena Text: entertainment and media13201373o3
LMArena Vision: English11881221o3
LMArena Vision: Chinese11641237o3
LMArena Vision: reading text11561218o3
LMArena Vision: humor11661222o3
LMArena Vision: captioning11511210o3
LMArena Vision: recognizing things11961234o3
LMArena Vision: creative writing11771201o3
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 Gemma 3 27B and o3
BenchmarkGemma 3 27Bo3Leader
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
o3$0.0060Fits in one request

Gemma 3 27B costs less

Repository review

50K input + 3K output tokens

Gemma 3 27B$0.0049Fits in one request
o3$0.124Fits in one request

Gemma 3 27B costs less

Agent loop

200K input + 10K output tokens

Gemma 3 27B$0.019Exceeds the context window
o3$0.480Exceeds the context window

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 o3
SpecificationGoogle Gemma 3 27BOpenAI o3
MakerGoogleOpenAI
WeightsOpen weightsNo public weights listed
ReleasedMarch 12, 2025April 16, 2025
Context window131K200K
Input $/Mtok$0.08$2.00
Output $/Mtok$0.30$8.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computable$0.571
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 3 27B better than o3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 27B for output tokens 26.7x cheaper ($0.30 vs $8.00 per million) and work measured by Aider polyglot or LiveCodeBench (Artificial Analysis run), where it leads.

Which is cheaper, Gemma 3 27B or o3?

Gemma 3 27B costs $0.08 per million input tokens and $0.30 per million output tokens; o3 costs $2.00 and $8.00. Cost per solved task is known for o3 only.

Which has the bigger context window, Gemma 3 27B or o3?

o3, with 200K tokens against 131K.

How many benchmarks is the Gemma 3 27B vs o3 comparison based on?

63 benchmarks have a result for both models as of October 22, 2026. Gemma 3 27B's coding index rests on 0 independent benchmarks and o3's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next