Model comparison
Gemma 3 12B vs GPT-4.1
GPT-4.1 is the stronger model overall, scoring 35.9 to 32.1 on the Noometry Index. Gemma 3 12B costs 47× less per token, which makes it the better buy when GPT-4.1's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
GoogleSummary
- They share 21 benchmarks with published results for both. Gemma 3 12B scores higher in 3 categories and GPT-4.1 in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GPT-4.1 leads 37.1 to 26.5.
- The biggest single-benchmark swing is GPQA Diamond: 39.5% for Gemma 3 12B and 66.9% for GPT-4.1.
- Gemma 3 12B is cheaper at $0.05 / $0.15 per million input/output tokens, against $2 / $8 for GPT-4.1.
- GPT-4.1 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 | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 32.1 | 35.9 |
| Released | 2025-03-12 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 8K | 33K |
| Input $ / M tokens | $0.05 | $2 |
| Output $ / M tokens | $0.15 | $8 |
| Results tracked | 24 | 52 |
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Category by category
Coding GPT-4.1 leads
Gemma 3 12B: 31.7 (#280), GPT-4.1: 34.4 (#238)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| LMArena Coding | 1281 | 1391 |
| SWE-bench Verified | — | 48.5% |
| SWE-bench Verified (bash only) | — | 39.6% |
| Aider Polyglot | — | 52.4% |
| SciCode | 17.4% | — |
| WeirdML | — | 39% |
| CadEval | — | 42% |
| ALE-Bench | — | 558.1 |
Agentic & Tool Use GPT-4.1 leads
Gemma 3 12B: 25.5 (#108), GPT-4.1: 34.7 (#43)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 30.4% | 54% |
Reasoning Gemma 3 12B leads
Gemma 3 12B: 15.7 (#313), GPT-4.1: 11.7 (#339)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| Chess Puzzles | 0% | 6% |
| LMArena Hard Prompts | 1309 | 1384 |
| DTBench | 48.8% | 68.3% |
| LMCA | 4.5% | 25.6% |
| Epoch Capabilities Index | 123.5 | 136.78 |
| ARC-AGI-2 | — | 0.4% |
| SimpleBench | — | 27% |
| Kagi LLM Benchmark | — | 52.3% |
| ARC-AGI-1 | — | 5.5% |
| CritPt | 0% | — |
| EnigmaEval | — | 2.2% |
| ForecastBench | — | 61.5 |
Math Too close to call
Gemma 3 12B: 22.3 (#279), GPT-4.1: 22.3 (#280)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.7% | 38.3% |
| LMArena Math | 1307 | 1370 |
| FrontierMath (Tiers 1-3) | — | 6% |
| Omni-MATH | — | 47.1% |
| MATH Level 5 | — | 83% |
| FrontierMath (Feb 2025 set) | — | 5.5% |
| FrontierMath Tier 4 (v1) | — | 0% |
Knowledge GPT-4.1 leads
Gemma 3 12B: 26.5 (#257), GPT-4.1: 37.1 (#160)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| GPQA Diamond | 39.5% | 66.9% |
| Vectara Hallucination Rate | 4.4% | 5.6% |
| LMArena Expert | 1248 | 1364 |
| Humanity's Last Exam | — | 5.4% |
| SimpleQA Verified | — | 31.1% |
| MMLU-Pro | — | 81.1% |
| GPQA (HELM) | — | 65.9% |
Multimodal Not comparable
Gemma 3 12B: —, GPT-4.1: 38.2 (#67)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| LMArena Vision | — | 1211 |
| GeoBench | — | 72% |
| MindCube | 46.7% | — |
Multilingual GPT-4.1 leads
Gemma 3 12B: 45.7 (#165), GPT-4.1: 49.4 (#133)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| LMArena Non-English | 1318 | 1370 |
| LMArena German | 1370 | 1381 |
| LMArena Russian | 1335 | 1377 |
| LMArena Chinese | — | 1382 |
| LMArena French | — | 1382 |
| LMArena Japanese | — | 1319 |
| LMArena Korean | — | 1339 |
| LMArena Spanish | — | 1376 |
Instruction Following GPT-4.1 leads
Gemma 3 12B: 68.6 (#186), GPT-4.1: 71.3 (#153)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| LMArena Instruction Following | 1299 | 1367 |
| IFEval | — | 83.8% |
Long Context Too close to call
Gemma 3 12B: 40.0 (#162), GPT-4.1: 40.0 (#163)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| LMArena Longer Query | 1317 | 1385 |
| Fiction.LiveBench | — | 63.9% |
Writing & Preference GPT-4.1 leads
Gemma 3 12B: 47.5 (#209), GPT-4.1: 57.6 (#125)
| Benchmark | Gemma 3 12B | GPT-4.1 |
|---|---|---|
| LMArena Text | 1334 | 1383 |
| LMArena Creative Writing | 1331 | 1363 |
| EQ-Bench Creative Writing | 1126 | 1420 |
| LMArena Multi-Turn | 1334 | 1398 |
| WildBench | — | 85.4% |
Frequently asked questions
Is Gemma 3 12B better than GPT-4.1?
GPT-4.1 is the stronger model overall, scoring 35.9 to 32.1 on the Noometry Index. Gemma 3 12B costs 47× less per token, which makes it the better buy when GPT-4.1's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 12B or GPT-4.1?
Gemma 3 12B is cheaper. It lists at $0.05 per million input tokens and $0.15 per million output tokens; GPT-4.1 lists at $2 and $8.
Is Gemma 3 12B or GPT-4.1 better for coding?
GPT-4.1 scores higher on coding benchmarks: 34.4 versus 31.7 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 does, with 1.05M tokens against 131K.
How many benchmarks do Gemma 3 12B and GPT-4.1 share?
21 benchmarks have published results for both models. Gemma 3 12B has 24 scored results on Noometry and GPT-4.1 has 52.