Model comparison
Gemma 3 27B vs GPT-6 Sol
GPT-6 Sol is the stronger model overall, scoring 49.2 to 30.5 on the Noometry Index. Gemma 3 27B costs 40× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Last verified . 15 shared benchmarks.
GoogleSummary
- They share 15 benchmarks with published results for both. Gemma 3 27B scores higher in 0 categories and GPT-6 Sol in 10 categories; 10 gaps are clear of the uncertainty.
- The widest gap is in coding, where GPT-6 Sol leads 59.6 to 22.1.
- Gemma 3 27B is cheaper at $0.08 / $0.16 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 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 3 27B | GPT-6 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 30.5 | 49.2 |
| Released | 2025-03-11 | 2026-09-22 |
| Weights | Open | Proprietary |
| Context window | 131K | 1.05M |
| Max output | 8K | 128K |
| Input $ / M tokens | $0.08 | $2 |
| Output $ / M tokens | $0.16 | $10 |
| Results tracked | 43 | 22 |
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Category by category
Coding GPT-6 Sol leads
Gemma 3 27B: 22.1 (#329), GPT-6 Sol: 59.6 (#11)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Coding | 1322 | 1453 |
| DeepSWE | — | 68.8% |
| FrontierCode | — | 49.3% |
| Aider Polyglot | 4.9% | — |
| LMArena WebDev | — | 1692 |
| SciCode | 21.2% | — |
| LiveBench Coding | 39.9% | — |
Agentic & Tool Use GPT-6 Sol leads
Gemma 3 27B: 24.9 (#105), GPT-6 Sol: 33.5 (#49)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| Berkeley Function Calling Leaderboard | 29.5% | — |
| GDP.pdf | — | 28% |
Reasoning GPT-6 Sol leads
Gemma 3 27B: 16.3 (#297), GPT-6 Sol: 49.3 (#34)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Hard Prompts | 1340 | 1420 |
| Kagi LLM Benchmark | 40.4% | — |
| NYT Connections (extended) | — | 90.1% |
| CritPt | 0% | — |
| Chess Puzzles | 0% | — |
| EBR-Bench | — | 53.3% |
| LiveBench Reasoning | 43.8% | — |
| DTBench | 52.5% | — |
| LiveBench Data Analysis | 51.5% | — |
| LMCA | 12.3% | — |
| Epoch Capabilities Index | 130.04 | — |
| LiveBench | 50% | — |
Math GPT-6 Sol leads
Gemma 3 27B: 24.4 (#261), GPT-6 Sol: 35.8 (#135)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Math | 1312 | 1404 |
| OTIS Mock AIME 2024-2025 | 22.5% | — |
| LiveBench Math | 55.4% | — |
| MATH Level 5 | 74% | — |
Knowledge GPT-6 Sol leads
Gemma 3 27B: 25.4 (#256), GPT-6 Sol: 43.0 (#87)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| Vectara Hallucination Rate | 7.4% | 6.5% |
| LMArena Expert | 1303 | 1449 |
| GPQA Diamond | 47.7% | — |
| Confabulations | 40.3% | — |
Multimodal GPT-6 Sol leads
Gemma 3 27B: 32.0 (#94), GPT-6 Sol: 47.6 (#9)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Vision | 1165 | — |
| GeoBench | 52% | — |
| Furniture Assembly | — | 58.3% |
Multilingual GPT-6 Sol leads
Gemma 3 27B: 47.0 (#150), GPT-6 Sol: 51.0 (#113)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Non-English | 1334 | 1389 |
| LMArena Chinese | 1347 | 1416 |
| LMArena Russian | 1349 | 1407 |
| LMArena Spanish | 1348 | 1377 |
| LMArena French | 1368 | — |
| LMArena German | 1362 | — |
| LMArena Japanese | 1287 | — |
| LMArena Korean | 1308 | — |
Instruction Following GPT-6 Sol leads
Gemma 3 27B: 70.8 (#155), GPT-6 Sol: 74.4 (#97)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Instruction Following | 1321 | 1406 |
| LiveBench Instruction Following | 74.9% | — |
Long Context GPT-6 Sol leads
Gemma 3 27B: 27.6 (#288), GPT-6 Sol: 43.2 (#100)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Longer Query | 1333 | 1415 |
| Fiction.LiveBench | 33.3% | — |
Writing & Preference GPT-6 Sol leads
Gemma 3 27B: 52.7 (#161), GPT-6 Sol: 72.3 (#15)
| Benchmark | Gemma 3 27B | GPT-6 Sol |
|---|---|---|
| LMArena Text | 1358 | 1396 |
| LMArena Creative Writing | 1346 | 1392 |
| EQ-Bench Creative Writing | 1266 | 2125 |
| LMArena Multi-Turn | 1344 | 1405 |
| Short-Story Creative Writing | 79.9% | — |
| LiveBench Language | 34.6% | — |
Frequently asked questions
Is Gemma 3 27B better than GPT-6 Sol?
GPT-6 Sol is the stronger model overall, scoring 49.2 to 30.5 on the Noometry Index. Gemma 3 27B costs 40× 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 27B or GPT-6 Sol?
Gemma 3 27B is cheaper. It lists at $0.08 per million input tokens and $0.16 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is Gemma 3 27B or GPT-6 Sol better for coding?
GPT-6 Sol scores higher on coding benchmarks: 59.6 versus 22.1 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 27B and GPT-6 Sol share?
15 benchmarks have published results for both models. Gemma 3 27B has 43 scored results on Noometry and GPT-6 Sol has 22.