Gemma 3 12B vs GPT-4o
Gemma 3 12B costs 61.5x less per output token than GPT-4o ($0.1625 vs $10.00 per million). Updated October 21, 2026; 12 benchmarks have a result for both.
Gemma 3 12B or GPT-4o: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Gemma 3 12B for output tokens 61.5x cheaper ($0.1625 vs $10.00 per million) and a larger context window (131K against 128K tokens).
- Shared results
- 12
- Gemma 3 12B only
- 29
- GPT-4o only
- 14
- 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
No call
Only Gemma 3 12B has a AA Intelligence Index result, 3.8.
Directional only
Agentic work
AA Agentic Index
No call
Only Gemma 3 12B has a AA Agentic Index result, 0.1.
Directional only
Web design
Design Arena: websites
No call
Only GPT-4o has a Design Arena: websites result, 831.
Directional only
Long documents
Listed context window
Gemma 3 12B
Gemma 3 12B takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemma 3 12B
Gemma 3 12B $0.0002, GPT-4o $0.0075 per turn.
List prices
At a glance
- Coding index
- Gemma 3 12B not benchmarked, GPT-4o not benchmarked.
- Widest category
- General, 17.8 points apart on average over 4 shared benchmarks.
- Widest single gap
- Long context reasoning (AA-LCR): Gemma 3 12B 8.3% against GPT-4o 49.3%, 41.0 points apart on a 0 to 100 scale.
- Output price
- Gemma 3 12B $0.1625 against GPT-4o $10.00 per million output tokens, 61.5x apart.
- Context window
- Gemma 3 12B takes 131K tokens, GPT-4o 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 12B | Bars | GPT-4o | Ties |
|---|---|---|---|---|
| Coding | 0 | 2 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 1 | 1 | ||
| Math | 2 | 0 | ||
| Knowledge | 0 | 1 | ||
| General | 1 | 3 | ||
| All shared boards | 4 | 8 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 38.8% | Only GPT-4o measured |
| SWE-bench Lite | Not measured | 38.0% | Only GPT-4o measured |
| SWE-bench (full test set) | Not measured | 18.8% | Only GPT-4o measured |
| SWE-bench Multimodal | Not measured | 30.4% | Only GPT-4o measured |
| AA Coding Index | 5.8 | Not measured | Only Gemma 3 12B measured |
| LiveCodeBench (Artificial Analysis run) | 13.7% | 30.9% | GPT-4o |
| SciCode | 16.4% | Not measured | Only Gemma 3 12B measured |
| Terminal-Bench Hard (Artificial Analysis run) | 0.8% | 8.3% | GPT-4o |
| LMArena Text: coding | 1281 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: software and IT | 1313 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| AA Intelligence Index | 3.8 | Not measured | Only Gemma 3 12B measured |
| Epoch Capabilities Index | 123.5 | Not measured | Only Gemma 3 12B measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| AA Agentic Index | 0.1 | Not measured | Only Gemma 3 12B measured |
| τ²-Bench Telecom | 10.8% | 25.1% | GPT-4o |
| GDPval | Not measured | 9.9% | Only GPT-4o measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 34.9% | 54.3% | GPT-4o |
| Humanity's Last Exam (Artificial Analysis run) | 4.2% | 2.4% | Gemma 3 12B |
| GPQA Diamond (Epoch AI run) | 39.5% | Not measured | Only Gemma 3 12B measured |
| ARC-AGI | Not measured | 4.5% | Only GPT-4o measured |
| ARC-AGI-2 | Not measured | 0.0% | Only GPT-4o measured |
| LMArena Text: hard prompts | 1309 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: expert | 1248 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: hard prompts in English | 1318 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 13 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| AA Math Index | 18.3 | 6.0 | Gemma 3 12B |
| AIME 2025 (Artificial Analysis run) | 18.3% | 6.0% | Gemma 3 12B |
| OTIS Mock AIME | 16.7% | Not measured | Only Gemma 3 12B measured |
| LMArena Text: math | 1307 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: mathematical work | 1336 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 8 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | 59.5% | 74.8% | GPT-4o |
| MMLU | Not measured | 88.1% | Only GPT-4o measured |
| LMArena Text: science | 1366 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: medicine and healthcare | 1334 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: legal and government | 1381 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: business and finance | 1376 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 11 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 831 | Only GPT-4o measured |
| Design Arena: UI components | Not measured | 885 | Only GPT-4o measured |
| Design Arena: game dev | Not measured | 906 | Only GPT-4o measured |
| Design Arena: data viz | Not measured | 858 | Only GPT-4o measured |
| Design Arena: 3D | Not measured | 869 | Only GPT-4o measured |
| Design Arena: all code categories | Not measured | 861 | Only GPT-4o measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index13
| Benchmark | Gemma 3 12B | GPT-4o | Leader |
|---|---|---|---|
| IFBench | 36.7% | 34.3% | Gemma 3 12B |
| Long context reasoning (AA-LCR) | 8.3% | 49.3% | GPT-4o |
| DTBench | 48.8% | 64.5% | GPT-4o |
| LMCA | 4.5% | 16.6% | GPT-4o |
| LMArena Text | 1334 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: instruction following | 1299 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: creative writing | 1331 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: English | 1349 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: non-English | 1318 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: German | 1370 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: Russian | 1335 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: multi-turn | 1334 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: longer queries | 1317 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: writing and language | 1307 | Not measured | Only Gemma 3 12B measured |
| LMArena Text: entertainment and media | 1297 | Not measured | Only Gemma 3 12B measured |
| Neither model has a result on the other 31 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemma 3 12B | GPT-4o | 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 12B costs less
Repository review
50K input + 3K output tokens
Gemma 3 12B costs less
Agent loop
200K input + 10K output tokens
Gemma 3 12B 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 12B | OpenAI GPT-4o |
|---|---|---|
| Maker | OpenAI | |
| Weights | Open weights | No public weights listed |
| Released | March 13, 2025 | May 13, 2024 |
| Context window | 131K | 128K |
| Input $/Mtok | $0.075 | $2.50 |
| Output $/Mtok | $0.1625 | $10.00 |
| 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 12B better than GPT-4o for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Gemma 3 12B for output tokens 61.5x cheaper ($0.1625 vs $10.00 per million) and a larger context window (131K against 128K tokens).
Which is cheaper, Gemma 3 12B or GPT-4o?
Gemma 3 12B costs $0.075 per million input tokens and $0.1625 per million output tokens; GPT-4o costs $2.50 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Gemma 3 12B or GPT-4o?
Gemma 3 12B, with 131K tokens against 128K.
How many benchmarks is the Gemma 3 12B vs GPT-4o comparison based on?
12 benchmarks have a result for both models as of October 21, 2026. Gemma 3 12B's coding index rests on 0 independent benchmarks and GPT-4o's on 0. Where only one model has a result, the page says so instead of naming a winner.