Model comparison
Gemma 2 9B vs GPT-5.6 Sol
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 25.7 on the Noometry Index.
Last verified . 21 shared benchmarks.
GoogleSummary
- They share 21 benchmarks with published results for both. Gemma 2 9B scores higher in 0 categories and GPT-5.6 Sol in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-5.6 Sol leads 85.5 to 9.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.6% for Gemma 2 9B and 100% for GPT-5.6 Sol.
- Gemma 2 9B has downloadable open weights; the other is API-only.
Side by side
| Gemma 2 9B | GPT-5.6 Sol | |
|---|---|---|
| Provider | OpenAI | |
| Noometry Index | 25.7 | 64.4 |
| Released | 2024-06-24 | 2026-07-09 |
| Weights | Open | Proprietary |
| Context window | — | 1.05M |
| Max output | — | 128K |
| Input $ / M tokens | — | $4 |
| Output $ / M tokens | — | $20 |
| Results tracked | 35 | 64 |
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Category by category
Coding GPT-5.6 Sol leads
Gemma 2 9B: 29.0 (#299), GPT-5.6 Sol: 61.1 (#7)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| LMArena Coding | 1174 | 1493 |
| DeepSWE | — | 72.7% |
| FrontierCode | — | 47.5% |
| CursorBench | — | 41.7% |
| LMArena WebDev | — | 1619 |
| FrontierSWE | — | 32.2% |
| SciCode | — | 57.1% |
| WeirdML | — | 89.4% |
| BigCodeBench Instruct | 34.7% | — |
| LiveBench Coding | 22.5% | — |
| MirrorCode | — | 20% |
| BigCodeBench Complete | 40.6% | — |
| ALE-Bench | — | 2,177 |
Agentic & Tool Use Not comparable
Gemma 2 9B: —, GPT-5.6 Sol: 50.2 (#7)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| APEX-Agents | — | 51.4% |
| OSWorld 2.0 | — | 27.3% |
| τ²-bench Banking | — | 46.9% |
| PostTrainBench | — | 36.2% |
| BALROG | — | 60% |
| GBAEval | — | 52.6% |
| GDP.pdf | — | 30.7% |
| LMArena Search | — | 1257 |
| Vending-Bench 2 | — | 9,619 |
Reasoning GPT-5.6 Sol leads
Gemma 2 9B: 15.3 (#306), GPT-5.6 Sol: 74.7 (#6)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| LMArena Hard Prompts | 1172 | 1481 |
| Epoch Capabilities Index | 119.78 | 161.99 |
| ARC-AGI-2 | — | 92.5% |
| SimpleBench | — | 71.7% |
| Kagi LLM Benchmark | — | 67% |
| NYT Connections (extended) | — | 93.8% |
| ARC-AGI-1 | — | 97.5% |
| CritPt | — | 32.3% |
| Chess Puzzles | — | 64% |
| EnigmaEval | — | 37.1% |
| EBR-Bench | — | 44.8% |
| LiveBench Reasoning | 15.2% | — |
| Mystery Game Puzzles | — | 58% |
| DTBench | — | 96% |
| LiveBench Data Analysis | 36.4% | — |
| LMCA | — | 59.2% |
| Surface Evolver Bench | — | 93.1% |
| Bench to the Future 3 | — | 0.14 |
| LiveBench | 28.7% | — |
| PIQA | 83.7% | — |
Math GPT-5.6 Sol leads
Gemma 2 9B: 9.3 (#312), GPT-5.6 Sol: 85.5 (#7)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.6% | 100% |
| LMArena Math | 1183 | 1472 |
| FrontierMath (Tiers 1-3) | — | 89.1% |
| FrontierMath Tier 4 | — | 82.9% |
| ProofBench | — | 83% |
| LiveBench Math | 19.8% | — |
| MATH Level 5 | 21% | — |
| FrontierMath Erdős | — | 0% |
| GSM8K | 84.9% | — |
Knowledge GPT-5.6 Sol leads
Gemma 2 9B: 9.7 (#300), GPT-5.6 Sol: 64.3 (#16)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| GPQA Diamond | 27.5% | 93.5% |
| LMArena Expert | 1147 | 1517 |
| SimpleQA Verified | — | 69.7% |
| Vectara Hallucination Rate | — | 12.4% |
| BoolQ | 85.7% | — |
| MMLU | 72.1% | — |
Multimodal Not comparable
Gemma 2 9B: —, GPT-5.6 Sol: 48.9 (#8)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| LMArena Vision | — | 1281 |
| Blueprint-Bench 2 | — | 33.6% |
| Furniture Assembly | — | 56.7% |
| LMArena Document | — | 1483 |
Multilingual GPT-5.6 Sol leads
Gemma 2 9B: 36.8 (#233), GPT-5.6 Sol: 55.4 (#32)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| LMArena Non-English | 1188 | 1450 |
| LMArena Chinese | 1185 | 1523 |
| LMArena French | 1189 | 1475 |
| LMArena German | 1186 | 1476 |
| LMArena Japanese | 1144 | 1475 |
| LMArena Korean | 1137 | 1434 |
| LMArena Russian | 1200 | 1466 |
| LMArena Spanish | 1200 | 1449 |
Instruction Following GPT-5.6 Sol leads
Gemma 2 9B: 57.8 (#264), GPT-5.6 Sol: 77.8 (#16)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| LMArena Instruction Following | 1178 | 1480 |
| LiveBench Instruction Following | 52.6% | — |
Long Context GPT-5.6 Sol leads
Gemma 2 9B: 36.3 (#228), GPT-5.6 Sol: 45.3 (#42)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| LMArena Longer Query | 1197 | 1479 |
Writing & Preference GPT-5.6 Sol leads
Gemma 2 9B: 32.3 (#276), GPT-5.6 Sol: 73.5 (#12)
| Benchmark | Gemma 2 9B | GPT-5.6 Sol |
|---|---|---|
| LMArena Text | 1207 | 1456 |
| LMArena Creative Writing | 1206 | 1450 |
| EQ-Bench Creative Writing | 841 | 1972 |
| LMArena Multi-Turn | 1193 | 1456 |
| EQ-Bench 4 | — | 1250 |
| LiveBench Language | 25.5% | — |
Frequently asked questions
Is Gemma 2 9B better than GPT-5.6 Sol?
GPT-5.6 Sol is the stronger model overall, scoring 64.4 to 25.7 on the Noometry Index.
Is Gemma 2 9B or GPT-5.6 Sol better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 61.1 versus 29.0 in the Noometry coding category.
How many benchmarks do Gemma 2 9B and GPT-5.6 Sol share?
21 benchmarks have published results for both models. Gemma 2 9B has 35 scored results on Noometry and GPT-5.6 Sol has 64.