Model comparison
Gemma 3 12B vs GPT-4.1 mini
GPT-4.1 mini is the stronger model overall, scoring 33.6 to 32.1 on the Noometry Index. Gemma 3 12B costs 9.3× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
GoogleSummary
- They share 22 benchmarks with published results for both. Gemma 3 12B scores higher in 4 categories and GPT-4.1 mini in 5 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in long context, where Gemma 3 12B leads 40.0 to 31.8.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 16.7% for Gemma 3 12B and 44.7% for GPT-4.1 mini.
- Gemma 3 12B is cheaper at $0.05 / $0.15 per million input/output tokens, against $0.40 / $1.60 for GPT-4.1 mini.
- GPT-4.1 mini 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 mini | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 32.1 | 33.6 |
| Released | 2025-03-12 | 2025-04-14 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 8K | 33K |
| Input $ / M tokens | $0.05 | $0.40 |
| Output $ / M tokens | $0.15 | $1.60 |
| Results tracked | 24 | 47 |
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Category by category
Coding Gemma 3 12B leads
Gemma 3 12B: 31.7 (#280), GPT-4.1 mini: 30.6 (#293)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| SciCode | 17.4% | 40.4% |
| LMArena Coding | 1281 | 1367 |
| SWE-bench Verified (bash only) | — | 23.9% |
| Aider Polyglot | — | 32.4% |
| WeirdML | — | 37.6% |
| BigCodeBench Instruct | — | 48.9% |
| CadEval | — | 16% |
Agentic & Tool Use GPT-4.1 mini leads
Gemma 3 12B: 25.5 (#108), GPT-4.1 mini: 33.3 (#55)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| Berkeley Function Calling Leaderboard | 30.4% | 50.5% |
Reasoning Gemma 3 12B leads
Gemma 3 12B: 15.7 (#313), GPT-4.1 mini: 10.8 (#340)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| CritPt | 0% | 0% |
| Chess Puzzles | 0% | 7% |
| LMArena Hard Prompts | 1309 | 1349 |
| DTBench | 48.8% | 68.8% |
| LMCA | 4.5% | 21.1% |
| Epoch Capabilities Index | 123.5 | 135.01 |
| ARC-AGI-2 | — | 0% |
| Kagi LLM Benchmark | — | 48.6% |
| ARC-AGI-1 | — | 3.5% |
| Mystery Game Puzzles | — | 7% |
Math GPT-4.1 mini leads
Gemma 3 12B: 22.3 (#279), GPT-4.1 mini: 24.1 (#270)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.7% | 44.7% |
| LMArena Math | 1307 | 1343 |
| FrontierMath (Tiers 1-3) | — | 6.7% |
| Omni-MATH | — | 49.1% |
| MATH Level 5 | — | 87.3% |
| FrontierMath (Feb 2025 set) | — | 4.5% |
Knowledge GPT-4.1 mini leads
Gemma 3 12B: 26.5 (#257), GPT-4.1 mini: 34.7 (#194)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| GPQA Diamond | 39.5% | 65.8% |
| LMArena Expert | 1248 | 1338 |
| SimpleQA Verified | — | 12.7% |
| MMLU-Pro | — | 78.3% |
| Vectara Hallucination Rate | 4.4% | — |
| GPQA (HELM) | — | 61.4% |
Multimodal Not comparable
Gemma 3 12B: —, GPT-4.1 mini: 35.8 (#82)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| LMArena Vision | — | 1181 |
| MindCube | 46.7% | — |
Multilingual Too close to call
Gemma 3 12B: 45.7 (#165), GPT-4.1 mini: 45.7 (#166)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| LMArena Non-English | 1318 | 1318 |
| LMArena German | 1370 | 1351 |
| LMArena Russian | 1335 | 1324 |
| LMArena Chinese | — | 1329 |
| LMArena French | — | 1358 |
| LMArena Japanese | — | 1290 |
| LMArena Korean | — | 1298 |
| LMArena Spanish | — | 1319 |
Instruction Following GPT-4.1 mini leads
Gemma 3 12B: 68.6 (#186), GPT-4.1 mini: 73.7 (#118)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| LMArena Instruction Following | 1299 | 1333 |
| IFEval | — | 90.4% |
Long Context Gemma 3 12B leads
Gemma 3 12B: 40.0 (#162), GPT-4.1 mini: 31.8 (#275)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| LMArena Longer Query | 1317 | 1344 |
| Fiction.LiveBench | — | 44.4% |
Writing & Preference GPT-4.1 mini leads
Gemma 3 12B: 47.5 (#209), GPT-4.1 mini: 48.6 (#199)
| Benchmark | Gemma 3 12B | GPT-4.1 mini |
|---|---|---|
| LMArena Text | 1334 | 1340 |
| LMArena Creative Writing | 1331 | 1300 |
| EQ-Bench Creative Writing | 1126 | 1147 |
| LMArena Multi-Turn | 1334 | 1354 |
| WildBench | — | 83.8% |
Frequently asked questions
Is Gemma 3 12B better than GPT-4.1 mini?
GPT-4.1 mini is the stronger model overall, scoring 33.6 to 32.1 on the Noometry Index. Gemma 3 12B costs 9.3× less per token, which makes it the better buy when GPT-4.1 mini's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 12B or GPT-4.1 mini?
Gemma 3 12B is cheaper. It lists at $0.05 per million input tokens and $0.15 per million output tokens; GPT-4.1 mini lists at $0.40 and $1.60.
Is Gemma 3 12B or GPT-4.1 mini better for coding?
Gemma 3 12B scores higher on coding benchmarks: 31.7 versus 30.6 in the Noometry coding category.
Which has the bigger context window?
GPT-4.1 mini does, with 1.05M tokens against 131K.
How many benchmarks do Gemma 3 12B and GPT-4.1 mini share?
22 benchmarks have published results for both models. Gemma 3 12B has 24 scored results on Noometry and GPT-4.1 mini has 47.