Model comparison
Gemma 2 27B vs GPT-6 Sol
GPT-6 Sol is the stronger model overall, scoring 61.8 to 29.4 on the Noometry Index. Gemma 2 27B costs 6.2× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
GoogleSummary
- They share 22 benchmarks with published results for both. Gemma 2 27B scores higher in 0 categories and GPT-6 Sol in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Sol leads 87.2 to 10.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 1.4% for Gemma 2 27B and 100% for GPT-6 Sol.
- Gemma 2 27B is cheaper at $0.65 / $0.65 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 8K.
- Gemma 2 27B has downloadable open weights; the other is API-only.
Side by side
| Gemma 2 27B | GPT-6 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 29.4 | 61.8 |
| Released | 2024-06-24 | 2026-09-22 |
| Weights | Open | Proprietary |
| Context window | 8K | 1.05M |
| Max output | 2K | 128K |
| Input $ / M tokens | $0.65 | $2 |
| Output $ / M tokens | $0.65 | $10 |
| Results tracked | 34 | 45 |
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Category by category
Coding GPT-6 Sol leads
Gemma 2 27B: 34.1 (#246), GPT-6 Sol: 60.1 (#11)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| LMArena Coding | 1211 | 1447 |
| DeepSWE | — | 68.8% |
| FrontierCode | — | 49.3% |
| LMArena WebDev | — | 1688 |
| SciCode | — | 57.6% |
| BigCodeBench Instruct | 42.8% | — |
| LiveBench Coding | 36% | — |
| BigCodeBench Complete | 52.5% | — |
| ALE-Bench | — | 2,462 |
Agentic & Tool Use Not comparable
Gemma 2 27B: —, GPT-6 Sol: 37.2 (#36)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| APEX-Agents | — | 54.3% |
| GDP.pdf | — | 26.4% |
| Vending-Bench 2 | — | 14,428 |
Reasoning GPT-6 Sol leads
Gemma 2 27B: 15.3 (#315), GPT-6 Sol: 74.0 (#9)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| LMArena Hard Prompts | 1198 | 1418 |
| DTBench | 48% | 97.3% |
| LMCA | 7.1% | 59.1% |
| Epoch Capabilities Index | 122.08 | 162.72 |
| ARC-AGI-2 | — | 89.6% |
| NYT Connections (extended) | — | 90.1% |
| ARC-AGI-1 | — | 95.5% |
| CritPt | — | 30.9% |
| EBR-Bench | — | 53.3% |
| LiveBench Reasoning | 28.1% | — |
| Mystery Game Puzzles | — | 56% |
| LiveBench Data Analysis | 47.9% | — |
| LiveBench | 38.2% | — |
Math GPT-6 Sol leads
Gemma 2 27B: 10.7 (#311), GPT-6 Sol: 87.2 (#7)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 1.4% | 100% |
| LMArena Math | 1212 | 1402 |
| FrontierMath (Tiers 1-3) | — | 89.8% |
| FrontierMath Tier 4 | — | 90% |
| ProofBench | — | 83% |
| LiveBench Math | 26.5% | — |
| MATH Level 5 | 27.9% | — |
Knowledge GPT-6 Sol leads
Gemma 2 27B: 19.0 (#280), GPT-6 Sol: 64.8 (#15)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| GPQA Diamond | 36.5% | 94.3% |
| LMArena Expert | 1172 | 1439 |
| SimpleQA Verified | — | 60.7% |
| Confabulations | 27.1% | — |
| Vectara Hallucination Rate | — | 6.5% |
| MMLU | 75.7% | — |
Multimodal Not comparable
Gemma 2 27B: —, GPT-6 Sol: 47.6 (#10)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| LMArena Vision | — | 1245 |
| Blueprint-Bench 2 | — | 36.9% |
| Furniture Assembly | — | 58.3% |
Multilingual GPT-6 Sol leads
Gemma 2 27B: 38.6 (#226), GPT-6 Sol: 50.5 (#118)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| LMArena Non-English | 1217 | 1385 |
| LMArena Chinese | 1221 | 1405 |
| LMArena French | 1247 | 1410 |
| LMArena German | 1209 | 1390 |
| LMArena Japanese | 1175 | 1385 |
| LMArena Korean | 1174 | 1341 |
| LMArena Russian | 1234 | 1401 |
| LMArena Spanish | 1228 | 1384 |
Instruction Following GPT-6 Sol leads
Gemma 2 27B: 60.5 (#249), GPT-6 Sol: 74.5 (#94)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| LMArena Instruction Following | 1206 | 1412 |
| LiveBench Instruction Following | 58.1% | — |
Long Context GPT-6 Sol leads
Gemma 2 27B: 37.3 (#218), GPT-6 Sol: 43.1 (#108)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| LMArena Longer Query | 1231 | 1411 |
Writing & Preference GPT-6 Sol leads
Gemma 2 27B: 44.2 (#225), GPT-6 Sol: 71.9 (#18)
| Benchmark | Gemma 2 27B | GPT-6 Sol |
|---|---|---|
| LMArena Text | 1231 | 1395 |
| LMArena Creative Writing | 1241 | 1378 |
| LMArena Multi-Turn | 1224 | 1412 |
| EQ-Bench Creative Writing | — | 2125 |
| LiveBench Language | 32.6% | — |
Frequently asked questions
Is Gemma 2 27B better than GPT-6 Sol?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 29.4 on the Noometry Index. Gemma 2 27B costs 6.2× 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 2 27B or GPT-6 Sol?
Gemma 2 27B is cheaper. It lists at $0.65 per million input tokens and $0.65 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is Gemma 2 27B or GPT-6 Sol better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 8K.
How many benchmarks do Gemma 2 27B and GPT-6 Sol share?
22 benchmarks have published results for both models. Gemma 2 27B has 34 scored results on Noometry and GPT-6 Sol has 45.