Gemma 3 27B vs GPT-4o-mini
GPT-4o-mini leads Gemma 3 27B on the Artificial Analysis Intelligence Index, 6.7 to 4.9, and Gemma 3 27B costs 2.0x less per output token ($0.30 vs $0.60 per million). Updated October 21, 2026; 14 benchmarks have a result for both.
Gemma 3 27B or GPT-4o-mini: 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 2.0x cheaper ($0.30 vs $0.60 per million) and a larger context window (131K against 128K tokens).
- Shared results
- 14
- Gemma 3 27B only
- 52
- GPT-4o-mini only
- 15
- Like-for-like categories
- 6 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
GPT-4o-mini
GPT-4o-mini leads, 6.7 against 4.9.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemma 3 27B has a AA Agentic Index result, 0.1.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-4o-mini has a GPQA Diamond result, 44.2%.
Directional only
Math
AIME
No call
Only GPT-4o-mini has a AIME result, 11.5%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-4o-mini has a MMLU Pro result, 62.7%.
Directional only
Long documents
Listed context window
Gemma 3 27B
Gemma 3 27B takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 27B
Gemma 3 27B $0.0002, GPT-4o-mini $0.0004 per turn.
List prices
At a glance
- Coding index
- Gemma 3 27B not benchmarked, GPT-4o-mini not benchmarked.
- Widest category
- Math, 6.0 points apart on average over 2 shared benchmarks.
- Widest single gap
- LiveCodeBench (Artificial Analysis run): Gemma 3 27B 13.7% against GPT-4o-mini 23.4%, 9.7 points apart on a 0 to 100 scale.
- Output price
- Gemma 3 27B $0.30 against GPT-4o-mini $0.60 per million output tokens, 2.0x apart.
- Context window
- Gemma 3 27B takes 131K tokens, GPT-4o-mini 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.
| Category | Gemma 3 27B | Bars | GPT-4o-mini | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 1 | 1 | ||
| Reasoning | 3 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 1 | 0 | ||
| General | 2 | 1 | ||
| All shared boards | 9 | 5 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| Aider polyglot | 4.9% | Not measured | Only Gemma 3 27B measured |
| AA Coding Index | 10.1 | 11.4 | GPT-4o-mini |
| LiveCodeBench (Vals AI) | Not measured | 26.4% | Only GPT-4o-mini measured |
| LiveCodeBench (Artificial Analysis run) | 13.7% | 23.4% | GPT-4o-mini |
| SciCode | 23.3% | Not measured | Only Gemma 3 27B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 3.8% | Not measured | Only Gemma 3 27B measured |
| LMArena Text: coding | 1322 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: software and IT | 1354 | Not measured | Only Gemma 3 27B measured |
| SciCode | 0.0% | 1.5% | GPT-4o-mini |
| Neither model has a result on the other 30 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| AA Intelligence Index | 4.9 | 6.7 | GPT-4o-mini |
| Epoch Capabilities Index | 130.0 | 126.5 | Gemma 3 27B |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards, none shared
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| AA Agentic Index | 0.1 | Not measured | Only Gemma 3 27B measured |
| τ²-Bench Telecom | 10.5% | Not measured | Only Gemma 3 27B measured |
| Berkeley Function Calling Leaderboard (BFCL) | 29.5% | Not measured | Only Gemma 3 27B measured |
| Neither model has a result on the other 38 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 44.2% | Only GPT-4o-mini measured |
| MMMU Pro (Vals AI) | Not measured | 56.6% | Only GPT-4o-mini measured |
| GPQA Diamond (Artificial Analysis run) | 42.8% | 42.6% | Gemma 3 27B |
| Humanity's Last Exam (Artificial Analysis run) | 4.4% | 4.2% | Gemma 3 27B |
| GPQA Diamond (Epoch AI run) | 47.7% | Not measured | Only Gemma 3 27B measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4o-mini measured |
| LMArena Text: hard prompts | 1340 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: expert | 1304 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: hard prompts in English | 1353 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: diagrams | 1156 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: homework | 1160 | Not measured | Only Gemma 3 27B measured |
| Kagi LLM Benchmark | 35.1% | 28.8% | Gemma 3 27B |
| Neither model has a result on the other 10 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| AIME | Not measured | 11.5% | Only GPT-4o-mini measured |
| MATH 500 (Vals AI) | Not measured | 72.6% | Only GPT-4o-mini measured |
| MGSM (Vals AI) | Not measured | 86.2% | Only GPT-4o-mini measured |
| AA Math Index | 20.7 | 14.7 | Gemma 3 27B |
| AIME 2025 (Artificial Analysis run) | 20.7% | 14.7% | Gemma 3 27B |
| OTIS Mock AIME | 22.5% | Not measured | Only Gemma 3 27B measured |
| MATH level 5 | 74.0% | Not measured | Only Gemma 3 27B measured |
| GSM8K | Not measured | 91.3% | Only GPT-4o-mini measured |
| LMArena Text: math | 1312 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: mathematical work | 1327 | Not measured | Only Gemma 3 27B measured |
| Neither model has a result on the other 3 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 62.7% | Only GPT-4o-mini measured |
| CorpFin (Vals AI) | Not measured | 45.5% | Only GPT-4o-mini measured |
| TaxEval (Vals AI) | Not measured | 60.5% | Only GPT-4o-mini measured |
| MortgageTax (Vals AI) | Not measured | 54.5% | Only GPT-4o-mini measured |
| MedQA (Vals AI) | Not measured | 72.4% | Only GPT-4o-mini measured |
| MMLU Pro (Artificial Analysis run) | 66.9% | 64.8% | Gemma 3 27B |
| MMLU | Not measured | 81.8% | Only GPT-4o-mini measured |
| GeoBench | 52.0% | Not measured | Only Gemma 3 27B measured |
| LMArena Text: science | 1383 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: medicine and healthcare | 1391 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: legal and government | 1375 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: business and finance | 1360 | Not measured | Only Gemma 3 27B measured |
| FACTS Benchmark Suite | 29.1% | Not measured | Only Gemma 3 27B measured |
| Neither model has a result on the other 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index21
| Benchmark | Gemma 3 27B | GPT-4o-mini | Leader |
|---|---|---|---|
| IFBench | 31.8% | 31.0% | Gemma 3 27B |
| Long context reasoning (AA-LCR) | 7.3% | Not measured | Only Gemma 3 27B measured |
| DTBench | 52.5% | 54.4% | GPT-4o-mini |
| LMCA | 12.3% | 10.4% | Gemma 3 27B |
| Fiction.LiveBench | 33.3% | Not measured | Only Gemma 3 27B measured |
| Creative writing (Lech Mazur) | 79.9% | Not measured | Only Gemma 3 27B measured |
| PIQA | Not measured | 88.7% | Only GPT-4o-mini measured |
| LMArena Text | 1358 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: instruction following | 1321 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: creative writing | 1345 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision | 1165 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: English | 1377 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: non-English | 1334 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: Chinese | 1346 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: German | 1362 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: Japanese | 1287 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: Korean | 1308 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: French | 1368 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: Spanish | 1349 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: Russian | 1349 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: Polish | 1345 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: multi-turn | 1345 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: longer queries | 1333 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: writing and language | 1347 | Not measured | Only Gemma 3 27B measured |
| LMArena Text: entertainment and media | 1320 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: English | 1188 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: Chinese | 1164 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: reading text | 1156 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: humor | 1166 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: captioning | 1151 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: recognizing things | 1196 | Not measured | Only Gemma 3 27B measured |
| LMArena Vision: creative writing | 1177 | Not measured | Only Gemma 3 27B measured |
| Neither model has a result on the other 14 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 27B | GPT-4o-mini | 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 3 27B costs less
Repository review
50K input + 3K output tokens
Gemma 3 27B costs less
Agent loop
200K input + 10K output tokens
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.
| Specification | Google Gemma 3 27B | OpenAI GPT-4o-mini |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | March 12, 2025 | July 18, 2024 |
| Context window | 131K | 128K |
| Input $/Mtok | $0.08 | $0.15 |
| Output $/Mtok | $0.30 | $0.60 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemma 3 27B better than GPT-4o-mini for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 27B for output tokens 2.0x cheaper ($0.30 vs $0.60 per million) and a larger context window (131K against 128K tokens).
Which is cheaper, Gemma 3 27B or GPT-4o-mini?
Gemma 3 27B costs $0.08 per million input tokens and $0.30 per million output tokens; GPT-4o-mini costs $0.15 and $0.60. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 3 27B or GPT-4o-mini?
Gemma 3 27B, with 131K tokens against 128K.
How many benchmarks is the Gemma 3 27B vs GPT-4o-mini comparison based on?
14 benchmarks have a result for both models as of October 21, 2026. Gemma 3 27B's coding index rests on 0 independent benchmarks and GPT-4o-mini's on 0. Where only one model has a result, the page says so instead of naming a winner.