Model comparison
Gemma 3 12B vs GPT-4.1 nano
Gemma 3 12B is the stronger model overall, scoring 31.8 to 27.7 on the Noometry Index.
Last verified . 21 shared benchmarks.
GoogleSummary
- They share 21 benchmarks with published results for both. Gemma 3 12B scores higher in 7 categories and GPT-4.1 nano in 2 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemma 3 12B leads 40.0 to 23.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 16.7% for Gemma 3 12B and 28.9% for GPT-4.1 nano.
- Gemma 3 12B is cheaper at $0.05 / $0.15 per million input/output tokens, against $0.10 / $0.40 for GPT-4.1 nano.
- GPT-4.1 nano accepts more context: 1.05M tokens versus 131K.
- Gemma 3 12B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 12B | GPT-4.1 nano | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 31.8 | 27.7 |
| Released | 2025-03-12 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 8K | 33K |
| Input $ / M tokens | $0.05 | $0.10 |
| Output $ / M tokens | $0.15 | $0.40 |
| Results tracked | 24 | 38 |
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Category by category
Coding Gemma 3 12B leads
Gemma 3 12B: 31.2 (#276), GPT-4.1 nano: 23.8 (#325)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| SciCode | 17.4% | 25.9% |
| LMArena Coding | 1281 | 1306 |
| Aider Polyglot | — | 8.9% |
| WeirdML | — | 19% |
Agentic & Tool Use GPT-4.1 nano leads
Gemma 3 12B: 25.3 (#101), GPT-4.1 nano: 26.3 (#98)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| Berkeley Function Calling Leaderboard | 30.4% | 33% |
Reasoning Gemma 3 12B leads
Gemma 3 12B: 15.2 (#307), GPT-4.1 nano: 8.6 (#344)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| CritPt | 0% | 0% |
| LMArena Hard Prompts | 1309 | 1286 |
| DTBench | 48.8% | 52.5% |
| LMCA | 4.5% | 5.5% |
| Epoch Capabilities Index | 123.49 | 129.62 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 33.3% |
| ARC-AGI-1 | — | 0% |
| Chess Puzzles | 0% | — |
Math GPT-4.1 nano leads
Gemma 3 12B: 21.0 (#273), GPT-4.1 nano: 25.5 (#246)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.7% | 28.9% |
| LMArena Math | 1307 | 1274 |
| Omni-MATH | — | 36.7% |
| MATH Level 5 | — | 70% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge Gemma 3 12B leads
Gemma 3 12B: 26.5 (#250), GPT-4.1 nano: 21.8 (#268)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| GPQA Diamond | 39.5% | 48.9% |
| LMArena Expert | 1248 | 1272 |
| SimpleQA Verified | — | 6% |
| MMLU-Pro | — | 55% |
| Vectara Hallucination Rate | 4.4% | — |
| GPQA (HELM) | — | 50.7% |
Multimodal Not comparable
Gemma 3 12B: —, GPT-4.1 nano: 28.6 (#108)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| LMArena Vision | — | 1063 |
| MindCube | 46.7% | — |
Multilingual Gemma 3 12B leads
Gemma 3 12B: 45.9 (#160), GPT-4.1 nano: 41.8 (#200)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| LMArena Non-English | 1318 | 1260 |
| LMArena German | 1370 | 1288 |
| LMArena Russian | 1335 | 1261 |
| LMArena Chinese | — | 1270 |
| LMArena Japanese | — | 1199 |
Instruction Following Too close to call
Gemma 3 12B: 68.8 (#179), GPT-4.1 nano: 68.0 (#188)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| LMArena Instruction Following | 1299 | 1267 |
| IFEval | — | 84.3% |
Long Context Gemma 3 12B leads
Gemma 3 12B: 40.0 (#157), GPT-4.1 nano: 23.7 (#291)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| LMArena Longer Query | 1317 | 1283 |
| Fiction.LiveBench | — | 25% |
Writing & Preference Gemma 3 12B leads
Gemma 3 12B: 47.7 (#205), GPT-4.1 nano: 40.7 (#238)
| Benchmark | Gemma 3 12B | GPT-4.1 nano |
|---|---|---|
| LMArena Text | 1334 | 1285 |
| LMArena Creative Writing | 1331 | 1260 |
| EQ-Bench Creative Writing | 1126 | 946 |
| LMArena Multi-Turn | 1334 | 1277 |
| WildBench | — | 81.2% |
Frequently asked questions
Is Gemma 3 12B better than GPT-4.1 nano?
Gemma 3 12B is the stronger model overall, scoring 31.8 to 27.7 on the Noometry Index.
Which is cheaper, Gemma 3 12B or GPT-4.1 nano?
Gemma 3 12B is cheaper. It lists at $0.05 per million input tokens and $0.15 per million output tokens; GPT-4.1 nano lists at $0.10 and $0.40.
Is Gemma 3 12B or GPT-4.1 nano better for coding?
Gemma 3 12B scores higher on coding benchmarks: 31.2 versus 23.8 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 nano does, with 1.05M tokens against 131K.
How many benchmarks do Gemma 3 12B and GPT-4.1 nano share?
21 benchmarks have published results for both models. Gemma 3 12B has 24 scored results on Noometry and GPT-4.1 nano has 38.