Model comparison
GPT-5.6 Sol vs o3-pro
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 42.9 on the Noometry Index.
Last verified . 8 shared benchmarks.
Summary
- They share 8 benchmarks with published results for both. GPT-5.6 Sol scores higher in 4 categories and o3-pro in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-5.6 Sol leads 74.8 to 23.8.
- The biggest single-benchmark swing is ARC-AGI-2: 92.5% for GPT-5.6 Sol and 4.9% for o3-pro.
- GPT-5.6 Sol is cheaper at $4 / $20 per million input/output tokens, against $20 / $80 for o3-pro.
- GPT-5.6 Sol accepts more context: 1.05M tokens versus 200K.
Side by side
| GPT-5.6 Sol | o3-pro | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 65.0 | 42.9 |
| Released | 2026-07-09 | 2025-06-10 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $4 | $20 |
| Output $ / M tokens | $20 | $80 |
| Results tracked | 65 | 12 |
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Category by category
Coding GPT-5.6 Sol leads
GPT-5.6 Sol: 65.1 (#7), o3-pro: 55.5 (#24)
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| WeirdML | 89.4% | 58.2% |
| DeepSWE | 72.7% | — |
| FrontierCode | 47.5% | — |
| Aider Polyglot | — | 84.9% |
| CursorBench | 41.7% | — |
| LMArena WebDev | 1618 | — |
| FrontierSWE | 32.2% | — |
| SciCode | 57.1% | — |
| GSO | 76.5% | — |
| LMArena Coding | 1498 | — |
| MirrorCode | 20% | — |
| ALE-Bench | 2,177 | — |
Agentic & Tool Use Not comparable
GPT-5.6 Sol: 50.3 (#7), o3-pro: —
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| 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
GPT-5.6 Sol: 74.8 (#8), o3-pro: 23.8 (#171)
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| ARC-AGI-2 | 92.5% | 4.9% |
| Kagi LLM Benchmark | 67% | 72.1% |
| ARC-AGI-1 | 97.5% | 59.3% |
| DTBench | 96% | 86.9% |
| LMCA | 59.2% | 38.5% |
| Epoch Capabilities Index | 161.66 | 147.42 |
| SimpleBench | 71.7% | — |
| NYT Connections (extended) | 93.8% | — |
| CritPt | 32.3% | — |
| Chess Puzzles | 64% | — |
| EnigmaEval | 37.1% | — |
| EBR-Bench | 44.8% | — |
| LMArena Hard Prompts | 1484 | — |
| Mystery Game Puzzles | 58% | — |
| Surface Evolver Bench | 93.1% | — |
| Bench to the Future 3 | 0.14 | — |
Math Not comparable
GPT-5.6 Sol: 85.6 (#9), o3-pro: —
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| FrontierMath (Tiers 1-3) | 89.1% | — |
| FrontierMath Tier 4 | 82.9% | — |
| OTIS Mock AIME 2024-2025 | 100% | — |
| ProofBench | 83% | — |
| LMArena Math | 1474 | — |
| FrontierMath Erdős | 0% | — |
Knowledge GPT-5.6 Sol leads
GPT-5.6 Sol: 64.3 (#18), o3-pro: 29.5 (#238)
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| Vectara Hallucination Rate | 12.4% | 23.3% |
| GPQA Diamond | 93.5% | — |
| SimpleQA Verified | 69.7% | — |
| Confabulations | — | 14.2% |
| LMArena Expert | 1516 | — |
Multimodal Not comparable
GPT-5.6 Sol: 48.6 (#9), o3-pro: —
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| LMArena Vision | 1281 | — |
| Blueprint-Bench 2 | 33.6% | — |
| Furniture Assembly | 56.7% | — |
| LMArena Document | 1483 | — |
Multilingual Not comparable
GPT-5.6 Sol: 55.3 (#32), o3-pro: —
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| LMArena Non-English | 1452 | — |
| LMArena Chinese | 1527 | — |
| LMArena French | 1477 | — |
| LMArena German | 1476 | — |
| LMArena Japanese | 1471 | — |
| LMArena Korean | 1442 | — |
| LMArena Russian | 1468 | — |
| LMArena Spanish | 1441 | — |
Instruction Following Not comparable
GPT-5.6 Sol: 77.7 (#16), o3-pro: —
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1482 | — |
Long Context o3-pro leads
GPT-5.6 Sol: 45.4 (#42), o3-pro: 72.2 (#1)
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1480 | — |
Writing & Preference GPT-5.6 Sol leads
GPT-5.6 Sol: 73.3 (#12), o3-pro: 57.1 (#133)
| Benchmark | GPT-5.6 Sol | o3-pro |
|---|---|---|
| LMArena Text | 1457 | — |
| LMArena Creative Writing | 1448 | — |
| Short-Story Creative Writing | — | 84.4% |
| EQ-Bench Creative Writing | 1972 | — |
| EQ-Bench 4 | 1250 | — |
| LMArena Multi-Turn | 1460 | — |
Frequently asked questions
Is GPT-5.6 Sol better than o3-pro?
GPT-5.6 Sol is the stronger model overall, scoring 65.0 to 42.9 on the Noometry Index.
Which is cheaper, GPT-5.6 Sol or o3-pro?
GPT-5.6 Sol is cheaper. It lists at $4 per million input tokens and $20 per million output tokens; o3-pro lists at $20 and $80.
Is GPT-5.6 Sol or o3-pro better for coding?
GPT-5.6 Sol scores higher on coding benchmarks: 65.1 versus 55.5 in the Noometry coding category.
Which has the bigger context window?
GPT-5.6 Sol does, with 1.05M tokens against 200K.
How many benchmarks do GPT-5.6 Sol and o3-pro share?
8 benchmarks have published results for both models. GPT-5.6 Sol has 65 scored results on Noometry and o3-pro has 12.