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Gemma 2 27B vs GPT-4o (2024-08-06)

Gemma 2 27B costs 15.4x less per output token than GPT-4o (2024-08-06) ($0.65 vs $10.00 per million). Updated October 22, 2026; 32 benchmarks have a result for both.

Replace Gemma 2 27B Replace GPT-4o (2024-08-06)
Gemma 2 27BGoogle
Coding
No data
Overall
No data
Output $/M
$0.65
0
GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
32
vs boards won of 32 shared

Gemma 2 27B or GPT-4o (2024-08-06): which to pick

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

Pick Gemma 2 27B for output tokens 15.4x cheaper ($0.65 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AGemma 2 27BGoogleNot benchmarkedNo coding benchmarkNo cost per solved taskModel BGPT-4o (2024-08-06)OpenAINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
32
Gemma 2 27B only
4
GPT-4o (2024-08-06) only
26
Like-for-like categories
5 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 2 27B not benchmarked, GPT-4o (2024-08-06) not benchmarked.
Widest category
Math, 13.2 points apart on average over 4 shared benchmarks.
Widest single gap
MATH level 5: Gemma 2 27B 27.9% against GPT-4o (2024-08-06) 53.3%, 25.4 points apart on a 0 to 100 scale.
Output price
Gemma 2 27B $0.65 against GPT-4o (2024-08-06) $10.00 per million output tokens, 15.4x apart.
Context window
Gemma 2 27B takes 8K tokens, GPT-4o (2024-08-06) 128K.

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 2 27BBarsGPT-4o (2024-08-06)Ties
Coding02
Reasoning04
Math04
Knowledge06
General016
All shared boards032
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
Aider polyglotNot measured23.1%Only GPT-4o (2024-08-06) measured
SWE-bench LiteNot measured21.7%Only GPT-4o (2024-08-06) measured
LiveCodeBench (Artificial Analysis run)Not measured31.7%Only GPT-4o (2024-08-06) measured
Terminal-Bench Hard (Artificial Analysis run)Not measured8.3%Only GPT-4o (2024-08-06) measured
LMArena Text: coding12111283GPT-4o (2024-08-06)
LMArena Text: software and IT12281278GPT-4o (2024-08-06)
Neither model has a result on the other 37 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
AA Intelligence IndexNot measured7.7Only GPT-4o (2024-08-06) measured
Epoch Capabilities Index122.1Not measuredOnly Gemma 2 27B measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
τ²-Bench TelecomNot measured28.9%Only GPT-4o (2024-08-06) measured
Neither model has a result on the other 41 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
MMMU Pro (Vals AI)Not measured64.0%Only GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)Not measured52.1%Only GPT-4o (2024-08-06) measured
Humanity's Last Exam (Artificial Analysis run)Not measured2.3%Only GPT-4o (2024-08-06) measured
GPQA Diamond (Epoch AI run)36.5%49.2%GPT-4o (2024-08-06)
SimpleBenchNot measured17.8%Only GPT-4o (2024-08-06) measured
Chess puzzlesNot measured6.0%Only GPT-4o (2024-08-06) measured
LMArena Text: hard prompts11981264GPT-4o (2024-08-06)
LMArena Text: expert11711241GPT-4o (2024-08-06)
LMArena Text: hard prompts in English12061277GPT-4o (2024-08-06)
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
AIMENot measured14.0%Only GPT-4o (2024-08-06) measured
MATH 500 (Vals AI)Not measured75.2%Only GPT-4o (2024-08-06) measured
MGSM (Vals AI)Not measured90.7%Only GPT-4o (2024-08-06) measured
OTIS Mock AIME1.4%6.4%GPT-4o (2024-08-06)
FrontierMath, tiers 1 to 3Not measured0.4%Only GPT-4o (2024-08-06) measured
MATH level 527.9%53.3%GPT-4o (2024-08-06)
LMArena Text: math12121285GPT-4o (2024-08-06)
LMArena Text: mathematical work12211283GPT-4o (2024-08-06)
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
Knowledge benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
MMLU ProNot measured74.1%Only GPT-4o (2024-08-06) measured
LegalBench (Vals AI)68.0%80.1%GPT-4o (2024-08-06)
CorpFin (Vals AI)Not measured39.4%Only GPT-4o (2024-08-06) measured
TaxEval (Vals AI)Not measured71.1%Only GPT-4o (2024-08-06) measured
MortgageTax (Vals AI)Not measured61.0%Only GPT-4o (2024-08-06) measured
MedQA (Vals AI)Not measured88.2%Only GPT-4o (2024-08-06) measured
SimpleQA VerifiedNot measured26.0%Only GPT-4o (2024-08-06) measured
MMLU75.7%84.3%GPT-4o (2024-08-06)
LMArena Text: science12281274GPT-4o (2024-08-06)
LMArena Text: medicine and healthcare11981252GPT-4o (2024-08-06)
LMArena Text: legal and government12411275GPT-4o (2024-08-06)
LMArena Text: business and finance12081232GPT-4o (2024-08-06)
Neither model has a result on the other 8 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
Neither model has a result on 9 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index016
General benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
IFBenchNot measured36.0%Only GPT-4o (2024-08-06) measured
Long context reasoning (AA-LCR)Not measured41.0%Only GPT-4o (2024-08-06) measured
DTBench48.0%Not measuredOnly Gemma 2 27B measured
LMCA7.1%Not measuredOnly Gemma 2 27B measured
LMArena Text12311283GPT-4o (2024-08-06)
LMArena Text: instruction following12061267GPT-4o (2024-08-06)
LMArena Text: creative writing12401274GPT-4o (2024-08-06)
LMArena VisionNot measured1065Only GPT-4o (2024-08-06) measured
LMArena Text: English12421297GPT-4o (2024-08-06)
LMArena Text: non-English12171262GPT-4o (2024-08-06)
LMArena Text: Chinese12211254GPT-4o (2024-08-06)
LMArena Text: German12091257GPT-4o (2024-08-06)
LMArena Text: Japanese11751234GPT-4o (2024-08-06)
LMArena Text: Korean11741218GPT-4o (2024-08-06)
LMArena Text: French12481263GPT-4o (2024-08-06)
LMArena Text: Spanish12281269GPT-4o (2024-08-06)
LMArena Text: Russian12341272GPT-4o (2024-08-06)
LMArena Text: Polish1277Not measuredOnly Gemma 2 27B measured
LMArena Text: multi-turn12241279GPT-4o (2024-08-06)
LMArena Text: longer queries12301283GPT-4o (2024-08-06)
LMArena Text: writing and language12491290GPT-4o (2024-08-06)
LMArena Text: entertainment and media12121267GPT-4o (2024-08-06)
LMArena Vision: EnglishNot measured1072Only GPT-4o (2024-08-06) measured
LMArena Vision: ChineseNot measured1009Only GPT-4o (2024-08-06) measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemma 2 27B and GPT-4o (2024-08-06)
BenchmarkGemma 2 27BGPT-4o (2024-08-06)Leader
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 2 27B$0.0010Fits in one request
GPT-4o (2024-08-06)$0.0075Fits in one request

Gemma 2 27B costs less

Repository review

50K input + 3K output tokens

Gemma 2 27B$0.034Exceeds the context window
GPT-4o (2024-08-06)$0.155Fits in one request

Gemma 2 27B costs less

Agent loop

200K input + 10K output tokens

Gemma 2 27B$0.137Exceeds the context window
GPT-4o (2024-08-06)$0.600Exceeds the context window

Gemma 2 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 2 27B and GPT-4o (2024-08-06)
SpecificationGoogle Gemma 2 27BOpenAI GPT-4o (2024-08-06)
MakerGoogleOpenAI
WeightsOpen weightsNo public weights listed
ReleasedJuly 13, 2024August 6, 2024
Context window8K128K
Input $/Mtok$0.65$2.50
Output $/Mtok$0.65$10.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemma 2 27B better than GPT-4o (2024-08-06) for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 2 27B for output tokens 15.4x cheaper ($0.65 vs $10.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Gemma 2 27B or GPT-4o (2024-08-06)?

Gemma 2 27B costs $0.65 per million input tokens and $0.65 per million output tokens; GPT-4o (2024-08-06) costs $2.50 and $10.00. Cost per solved task is known for neither of them.

Which has the bigger context window, Gemma 2 27B or GPT-4o (2024-08-06)?

GPT-4o (2024-08-06), with 128K tokens against 8K.

How many benchmarks is the Gemma 2 27B vs GPT-4o (2024-08-06) comparison based on?

32 benchmarks have a result for both models as of October 22, 2026. Gemma 2 27B's coding index rests on 0 independent benchmarks and GPT-4o (2024-08-06)'s on 0. Where only one model has a result, the page says so instead of naming a winner.

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