Model comparison
Gemma 3 12B vs GPT-6 Sol
GPT-6 Sol is the stronger model overall, scoring 61.8 to 32.1 on the Noometry Index. Gemma 3 12B costs 53× less per token, which makes it the better buy when GPT-6 Sol'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 0 categories and GPT-6 Sol in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Sol leads 87.2 to 22.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 16.7% for Gemma 3 12B and 100% for GPT-6 Sol.
- Gemma 3 12B is cheaper at $0.05 / $0.15 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol 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-6 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 32.1 | 61.8 |
| Released | 2025-03-12 | 2026-09-22 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 8K | 128K |
| Input $ / M tokens | $0.05 | $2 |
| Output $ / M tokens | $0.15 | $10 |
| Results tracked | 24 | 45 |
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Category by category
Coding GPT-6 Sol leads
Gemma 3 12B: 31.7 (#280), GPT-6 Sol: 60.1 (#11)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| SciCode | 17.4% | 57.6% |
| LMArena Coding | 1281 | 1447 |
| DeepSWE | — | 68.8% |
| FrontierCode | — | 49.3% |
| LMArena WebDev | — | 1688 |
| ALE-Bench | — | 2,462 |
Agentic & Tool Use GPT-6 Sol leads
Gemma 3 12B: 25.5 (#108), GPT-6 Sol: 37.2 (#36)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| APEX-Agents | — | 54.3% |
| Berkeley Function Calling Leaderboard | 30.4% | — |
| GDP.pdf | — | 26.4% |
| Vending-Bench 2 | — | 14,428 |
Reasoning GPT-6 Sol leads
Gemma 3 12B: 15.7 (#313), GPT-6 Sol: 74.0 (#9)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| CritPt | 0% | 30.9% |
| LMArena Hard Prompts | 1309 | 1418 |
| DTBench | 48.8% | 97.3% |
| LMCA | 4.5% | 59.1% |
| Epoch Capabilities Index | 123.5 | 162.72 |
| ARC-AGI-2 | — | 89.6% |
| NYT Connections (extended) | — | 90.1% |
| ARC-AGI-1 | — | 95.5% |
| Chess Puzzles | 0% | — |
| EBR-Bench | — | 53.3% |
| Mystery Game Puzzles | — | 56% |
Math GPT-6 Sol leads
Gemma 3 12B: 22.3 (#279), GPT-6 Sol: 87.2 (#7)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 16.7% | 100% |
| LMArena Math | 1307 | 1402 |
| FrontierMath (Tiers 1-3) | — | 89.8% |
| FrontierMath Tier 4 | — | 90% |
| ProofBench | — | 83% |
Knowledge GPT-6 Sol leads
Gemma 3 12B: 26.5 (#257), GPT-6 Sol: 64.8 (#15)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| GPQA Diamond | 39.5% | 94.3% |
| Vectara Hallucination Rate | 4.4% | 6.5% |
| LMArena Expert | 1248 | 1439 |
| SimpleQA Verified | — | 60.7% |
Multimodal Not comparable
Gemma 3 12B: —, GPT-6 Sol: 47.6 (#10)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| LMArena Vision | — | 1245 |
| Blueprint-Bench 2 | — | 36.9% |
| Furniture Assembly | — | 58.3% |
| MindCube | 46.7% | — |
Multilingual GPT-6 Sol leads
Gemma 3 12B: 45.7 (#165), GPT-6 Sol: 50.5 (#118)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| LMArena Non-English | 1318 | 1385 |
| LMArena German | 1370 | 1390 |
| LMArena Russian | 1335 | 1401 |
| LMArena Chinese | — | 1405 |
| LMArena French | — | 1410 |
| LMArena Japanese | — | 1385 |
| LMArena Korean | — | 1341 |
| LMArena Spanish | — | 1384 |
Instruction Following GPT-6 Sol leads
Gemma 3 12B: 68.6 (#186), GPT-6 Sol: 74.5 (#94)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| LMArena Instruction Following | 1299 | 1412 |
Long Context GPT-6 Sol leads
Gemma 3 12B: 40.0 (#162), GPT-6 Sol: 43.1 (#108)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| LMArena Longer Query | 1317 | 1411 |
Writing & Preference GPT-6 Sol leads
Gemma 3 12B: 47.5 (#209), GPT-6 Sol: 71.9 (#18)
| Benchmark | Gemma 3 12B | GPT-6 Sol |
|---|---|---|
| LMArena Text | 1334 | 1395 |
| LMArena Creative Writing | 1331 | 1378 |
| EQ-Bench Creative Writing | 1126 | 2125 |
| LMArena Multi-Turn | 1334 | 1412 |
Frequently asked questions
Is Gemma 3 12B better than GPT-6 Sol?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 32.1 on the Noometry Index. Gemma 3 12B costs 53× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Which is cheaper, Gemma 3 12B or GPT-6 Sol?
Gemma 3 12B is cheaper. It lists at $0.05 per million input tokens and $0.15 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is Gemma 3 12B or GPT-6 Sol better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 31.7 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 131K.
How many benchmarks do Gemma 3 12B and GPT-6 Sol share?
21 benchmarks have published results for both models. Gemma 3 12B has 24 scored results on Noometry and GPT-6 Sol has 45.