Model comparison
GPT-6 Sol vs o3-mini
GPT-6 Sol is the stronger model overall, scoring 61.8 to 36.7 on the Noometry Index. o3-mini costs 2.1× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Last verified . 30 shared benchmarks.
Summary
- They share 30 benchmarks with published results for both. GPT-6 Sol scores higher in 8 categories and o3-mini in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GPT-6 Sol leads 87.2 to 28.1.
- The biggest single-benchmark swing is FrontierMath Tier 4: 90% for GPT-6 Sol and 0% for o3-mini.
- o3-mini is cheaper at $1.10 / $4.40 per million input/output tokens, against $2 / $10 for GPT-6 Sol.
- GPT-6 Sol accepts more context: 1.05M tokens versus 200K.
Side by side
| GPT-6 Sol | o3-mini | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 61.8 | 36.7 |
| Released | 2026-09-22 | 2024-12-20 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $2 | $1.10 |
| Output $ / M tokens | $10 | $4.40 |
| Results tracked | 45 | 51 |
Sponsored placements are available on pages like this one. Advertise on Noometry
Category by category
Coding GPT-6 Sol leads
GPT-6 Sol: 60.1 (#11), o3-mini: 40.8 (#132)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| SciCode | 57.6% | 39.8% |
| LMArena Coding | 1447 | 1378 |
| DeepSWE | 68.8% | — |
| FrontierCode | 49.3% | — |
| Aider Polyglot | — | 60.4% |
| LMArena WebDev | 1688 | — |
| GSO | — | 1.3% |
| WeirdML | — | 43.7% |
| LiveBench Coding | — | 82.7% |
| CadEval | — | 54% |
| ALE-Bench | 2,462 | — |
Agentic & Tool Use GPT-6 Sol leads
GPT-6 Sol: 37.2 (#36), o3-mini: 29.6 (#84)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| APEX-Agents | 54.3% | — |
| Cybench | — | 22.5% |
| GDP.pdf | 26.4% | — |
| Vending-Bench 2 | 14,428 | — |
Reasoning GPT-6 Sol leads
GPT-6 Sol: 74.0 (#9), o3-mini: 16.3 (#305)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| ARC-AGI-2 | 89.6% | 3% |
| ARC-AGI-1 | 95.5% | 34.5% |
| CritPt | 30.9% | 0.3% |
| LMArena Hard Prompts | 1418 | 1366 |
| Mystery Game Puzzles | 56% | 7% |
| DTBench | 97.3% | 68.8% |
| LMCA | 59.1% | 19% |
| Epoch Capabilities Index | 162.72 | 140.34 |
| SimpleBench | — | 22.8% |
| NYT Connections (extended) | 90.1% | — |
| Chess Puzzles | — | 17% |
| EBR-Bench | 53.3% | — |
| LiveBench Reasoning | — | 89.6% |
| LiveBench Data Analysis | — | 70.6% |
| ForecastBench | — | 59.6 |
| LiveBench | — | 75.9% |
Math GPT-6 Sol leads
GPT-6 Sol: 87.2 (#7), o3-mini: 28.1 (#244)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| FrontierMath (Tiers 1-3) | 89.8% | 18.6% |
| FrontierMath Tier 4 | 90% | 0% |
| OTIS Mock AIME 2024-2025 | 100% | 76.9% |
| LMArena Math | 1402 | 1396 |
| ProofBench | 83% | — |
| LiveBench Math | — | 77.3% |
| MATH Level 5 | — | 96.5% |
| FrontierMath (Feb 2025 set) | — | 12.4% |
| FrontierMath Tier 4 (v1) | — | 4.2% |
Knowledge GPT-6 Sol leads
GPT-6 Sol: 64.8 (#15), o3-mini: 38.3 (#146)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| GPQA Diamond | 94.3% | 77% |
| SimpleQA Verified | 60.7% | 15.3% |
| LMArena Expert | 1439 | 1364 |
| Confabulations | — | 17.9% |
| Vectara Hallucination Rate | 6.5% | — |
Multimodal Not comparable
GPT-6 Sol: 47.6 (#10), o3-mini: —
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Vision | 1245 | — |
| Blueprint-Bench 2 | 36.9% | — |
| Furniture Assembly | 58.3% | — |
Multilingual GPT-6 Sol leads
GPT-6 Sol: 50.5 (#118), o3-mini: 45.7 (#164)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Non-English | 1385 | 1319 |
| LMArena Chinese | 1405 | 1379 |
| LMArena French | 1410 | 1334 |
| LMArena German | 1390 | 1303 |
| LMArena Japanese | 1385 | 1286 |
| LMArena Korean | 1341 | 1314 |
| LMArena Russian | 1401 | 1304 |
| LMArena Spanish | 1384 | 1321 |
Instruction Following Too close to call
GPT-6 Sol: 74.5 (#94), o3-mini: 75.1 (#72)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Instruction Following | 1412 | 1337 |
| LiveBench Instruction Following | — | 84.4% |
Long Context GPT-6 Sol leads
GPT-6 Sol: 43.1 (#108), o3-mini: 33.8 (#256)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Longer Query | 1411 | 1343 |
| Fiction.LiveBench | — | 50% |
Writing & Preference GPT-6 Sol leads
GPT-6 Sol: 71.9 (#18), o3-mini: 50.3 (#182)
| Benchmark | GPT-6 Sol | o3-mini |
|---|---|---|
| LMArena Text | 1395 | 1337 |
| LMArena Creative Writing | 1378 | 1286 |
| LMArena Multi-Turn | 1412 | 1320 |
| Short-Story Creative Writing | — | 61.7% |
| EQ-Bench Creative Writing | 2125 | — |
| LiveBench Language | — | 50.7% |
Frequently asked questions
Is GPT-6 Sol better than o3-mini?
GPT-6 Sol is the stronger model overall, scoring 61.8 to 36.7 on the Noometry Index. o3-mini costs 2.1× less per token, which makes it the better buy when GPT-6 Sol's lead doesn't matter for your workload.
Which is cheaper, GPT-6 Sol or o3-mini?
o3-mini is cheaper. It lists at $1.10 per million input tokens and $4.40 per million output tokens; GPT-6 Sol lists at $2 and $10.
Is GPT-6 Sol or o3-mini better for coding?
GPT-6 Sol scores higher on coding benchmarks: 60.1 versus 40.8 in the Noometry coding category.
Which has the bigger context window?
GPT-6 Sol does, with 1.05M tokens against 200K.
How many benchmarks do GPT-6 Sol and o3-mini share?
30 benchmarks have published results for both models. GPT-6 Sol has 45 scored results on Noometry and o3-mini has 51.