Model comparison
GPT-6 Luna vs o3-pro
GPT-6 Luna is the stronger model overall, scoring 45.1 to 42.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
Summary
- The widest gap is in long context, where o3-pro leads 72.1 to 43.3.
- GPT-6 Luna is cheaper at $0.10 / $0.50 per million input/output tokens, against $20 / $80 for o3-pro.
- GPT-6 Luna accepts more context: 1.05M tokens versus 200K.
Side by side
| GPT-6 Luna | o3-pro | |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 45.1 | 42.7 |
| Released | 2026-09-22 | 2025-06-10 |
| Weights | Proprietary | Proprietary |
| Context window | 1.05M | 200K |
| Max output | 128K | 100K |
| Input $ / M tokens | $0.10 | $20 |
| Output $ / M tokens | $0.50 | $80 |
| Results tracked | 18 | 12 |
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Category by category
Coding Too close to call
GPT-6 Luna: 54.7 (#24), o3-pro: 55.1 (#22)
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| DeepSWE | 66.6% | — |
| FrontierCode | 42.4% | — |
| Aider Polyglot | — | 84.9% |
| LMArena WebDev | 1583 | — |
| WeirdML | — | 58.2% |
| LMArena Coding | 1448 | — |
Reasoning GPT-6 Luna leads
GPT-6 Luna: 31.7 (#68), o3-pro: 24.1 (#152)
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| ARC-AGI-2 | — | 4.9% |
| Kagi LLM Benchmark | — | 72.1% |
| NYT Connections (extended) | 68.7% | — |
| ARC-AGI-1 | — | 59.3% |
| LMArena Hard Prompts | 1415 | — |
| DTBench | — | 86.9% |
| LMCA | — | 38.5% |
| Epoch Capabilities Index | — | 147.43 |
Math Not comparable
GPT-6 Luna: 35.6 (#140), o3-pro: —
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| LMArena Math | 1396 | — |
Knowledge GPT-6 Luna leads
GPT-6 Luna: 40.1 (#110), o3-pro: 29.0 (#234)
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| Confabulations | — | 14.2% |
| Vectara Hallucination Rate | — | 23.3% |
| LMArena Expert | 1458 | — |
Multimodal Not comparable
GPT-6 Luna: 42.0 (#27), o3-pro: —
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| Furniture Assembly | 44.2% | — |
Multilingual Not comparable
GPT-6 Luna: 51.0 (#111), o3-pro: —
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| LMArena Non-English | 1390 | — |
| LMArena Chinese | 1425 | — |
| LMArena Russian | 1392 | — |
| LMArena Spanish | 1416 | — |
Instruction Following Not comparable
GPT-6 Luna: 74.7 (#85), o3-pro: —
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| LMArena Instruction Following | 1414 | — |
Long Context o3-pro leads
GPT-6 Luna: 43.3 (#95), o3-pro: 72.1 (#1)
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| Fiction.LiveBench | — | 97.2% |
| LMArena Longer Query | 1417 | — |
Writing & Preference GPT-6 Luna leads
GPT-6 Luna: 58.4 (#115), o3-pro: 57.1 (#128)
| Benchmark | GPT-6 Luna | o3-pro |
|---|---|---|
| LMArena Text | 1392 | — |
| LMArena Creative Writing | 1357 | — |
| Short-Story Creative Writing | — | 84.4% |
| LMArena Multi-Turn | 1400 | — |
Frequently asked questions
Is GPT-6 Luna better than o3-pro?
GPT-6 Luna is the stronger model overall, scoring 45.1 to 42.7 on the Noometry Index.
Which is cheaper, GPT-6 Luna or o3-pro?
GPT-6 Luna is cheaper. It lists at $0.10 per million input tokens and $0.50 per million output tokens; o3-pro lists at $20 and $80.
Is GPT-6 Luna or o3-pro better for coding?
They score almost the same on coding (54.7 vs 55.1); test both on your own repository before choosing.
Which has the bigger context window?
GPT-6 Luna does, with 1.05M tokens against 200K.
How many benchmarks do GPT-6 Luna and o3-pro share?
0 benchmarks have published results for both models. GPT-6 Luna has 18 scored results on Noometry and o3-pro has 12.