# GPT-6 Astra vs o3

> GPT-6 Astra is the stronger model overall, scoring 70.8 to 47.5 on the Noometry Index. o3 costs 5.7× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gpt-6-astra-vs-o3
- Last updated: 2026-10-10
- Shared benchmarks: 35

## Summary

- They share 35 benchmarks with published results for both. GPT-6 Astra scores higher in 9 categories and o3 in 1 category; 10 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GPT-6 Astra leads 85.1 to 32.0.
- The biggest single-benchmark swing is ARC-AGI-2: 95% for GPT-6 Astra and 6.5% for o3.
- o3 is cheaper at $2 / $8 per million input/output tokens, against $10 / $50 for GPT-6 Astra.
- GPT-6 Astra accepts more context: 1.05M tokens versus 200K.

## Snapshot

| | GPT-6 Astra | o3 |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Noometry Index | 70.8 | 47.5 |
| Rank | 1 | 61 |
| Context | 1.05M | 200K |
| Input $/M | $10 | $2 |
| Output $/M | $50 | $8 |
| Weights | Proprietary | Proprietary |

## Coding

- GPT-6 Astra: 73.7 (#2)
- o3: 46.8 (#64)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| GSO | 79.4% | 8.8% |
| WeirdML | 93.6% | 52.4% |
| LMArena Coding | 1487 | 1408 |
| ALE-Bench | 2,951 | 933.55 |
| SWE-bench Verified | — | 62.3% |
| DeepSWE | 74.1% | — |
| FrontierCode | 53.3% | — |
| SWE-bench Verified (bash only) | — | 58.4% |
| Aider Polyglot | — | 81.3% |
| LMArena WebDev | 1786 | — |
| FrontierSWE | 65.5% | — |
| SciCode | 56.5% | — |
| MirrorCode | 46.7% | — |
| CadEval | — | 74% |

## Agentic & Tool Use

- GPT-6 Astra: 52.9 (#3)
- o3: 34.5 (#44)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| APEX-Agents | 64.7% | — |
| Berkeley Function Calling Leaderboard | — | 63% |
| GDPval | — | 30.8% |
| Remote Labor Index | 20.8% | — |
| DeepResearch Bench | — | 45.2% |
| OSWorld | — | 23% |
| BALROG | 68.3% | — |
| GDP.pdf | 34.2% | — |
| LMArena Search | — | 1144 |
| METR Time Horizons | — | 65.4% |
| Vending-Bench 2 | 15,515 | — |

## Reasoning

- GPT-6 Astra: 85.1 (#1)
- o3: 32.0 (#78)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| ARC-AGI-2 | 95% | 6.5% |
| ARC-AGI-1 | 98.5% | 60.8% |
| CritPt | 31.7% | 1.4% |
| Chess Puzzles | 72% | 38% |
| LMArena Hard Prompts | 1462 | 1402 |
| Mystery Game Puzzles | 84% | 29% |
| DTBench | 97.3% | 84.8% |
| LMCA | 64.4% | 39.7% |
| Epoch Capabilities Index | 166.45 | 146.86 |
| SimpleBench | — | 53.1% |
| Kagi LLM Benchmark | — | 67.6% |
| NYT Connections (extended) | 98.1% | — |
| EnigmaEval | — | 13.1% |
| EBR-Bench | 76.2% | — |
| Bench to the Future 3 | 0.14 | — |
| ForecastBench | — | 62.5 |

## Math

- GPT-6 Astra: 93.5 (#2)
- o3: 50.2 (#58)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 93.7% | 33.3% |
| OTIS Mock AIME 2024-2025 | 100% | 84.4% |
| LMArena Math | 1465 | 1426 |
| FrontierMath Tier 4 | 97.6% | — |
| ProofBench | 99% | — |
| Omni-MATH | — | 71.4% |
| MATH Level 5 | — | 97.8% |
| FrontierMath (Feb 2025 set) | — | 18.7% |
| FrontierMath Erdős | 2.9% | — |
| FrontierMath Tier 4 (v1) | — | 2.1% |

## Knowledge

- GPT-6 Astra: 75.3 (#1)
- o3: 54.6 (#52)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| GPQA Diamond | 95.8% | 81.8% |
| Humanity's Last Exam | 54.8% | 20.3% |
| SimpleQA Verified | 75.6% | 49.4% |
| LMArena Expert | 1483 | 1402 |
| MMLU-Pro | — | 85.9% |
| Confabulations | — | 14.4% |
| Vectara Hallucination Rate | 8.7% | — |
| GPQA (HELM) | — | 75.3% |

## Multimodal

- GPT-6 Astra: 55.0 (#3)
- o3: 41.4 (#36)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| LMArena Vision | 1281 | 1214 |
| GeoBench | — | 74% |
| VPCT | — | 52% |
| Blueprint-Bench 2 | 49.7% | — |
| Furniture Assembly | 80% | — |
| LMArena Document | 1468 | — |

## Multilingual

- GPT-6 Astra: 53.7 (#61)
- o3: 51.7 (#105)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| LMArena Non-English | 1430 | 1401 |
| LMArena Chinese | 1484 | 1437 |
| LMArena French | 1456 | 1430 |
| LMArena German | 1440 | 1420 |
| LMArena Japanese | 1379 | 1403 |
| LMArena Korean | 1426 | 1370 |
| LMArena Russian | 1436 | 1406 |
| LMArena Spanish | 1407 | 1395 |

## Instruction Following

- GPT-6 Astra: 76.3 (#44)
- o3: 72.8 (#127)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| LMArena Instruction Following | 1450 | 1368 |
| IFEval | — | 86.9% |

## Long Context

- GPT-6 Astra: 44.5 (#62)
- o3: 53.3 (#6)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| LMArena Longer Query | 1456 | 1372 |
| Fiction.LiveBench | — | 88.9% |
| CL-bench | — | 17.8% |

## Writing & Preference

- GPT-6 Astra: 75.3 (#7)
- o3: 63.5 (#64)

| Benchmark | GPT-6 Astra | o3 |
|---|---|---|
| LMArena Text | 1441 | 1410 |
| LMArena Creative Writing | 1418 | 1359 |
| EQ-Bench Creative Writing | 2173 | 1676 |
| LMArena Multi-Turn | 1448 | 1405 |
| Short-Story Creative Writing | — | 83.9% |
| WildBench | — | 86.1% |

## FAQ

### Is GPT-6 Astra better than o3?

GPT-6 Astra is the stronger model overall, scoring 70.8 to 47.5 on the Noometry Index. o3 costs 5.7× less per token, which makes it the better buy when GPT-6 Astra's lead doesn't matter for your workload.

### Which is cheaper, GPT-6 Astra or o3?

o3 is cheaper. It lists at $2 per million input tokens and $8 per million output tokens; GPT-6 Astra lists at $10 and $50.

### Is GPT-6 Astra or o3 better for coding?

GPT-6 Astra scores higher on coding benchmarks: 73.7 versus 46.8 in the Noometry coding category.

### Which has the bigger context window?

GPT-6 Astra does, with 1.05M tokens against 200K.

### How many benchmarks do GPT-6 Astra and o3 share?

35 benchmarks have published results for both models. GPT-6 Astra has 56 scored results on Noometry and o3 has 63.