OpenAI, proprietary

# GPT-6 Astra

> GPT-6 Astra by OpenAI, released September 2026. Ranked #1 of 354 with a Noometry Index of 70.8. API: $10 in / $50 out per M tokens. 1.05M context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/gpt-6-astra
- Last updated: 2026-10-10
- Title: GPT-6 Astra Benchmarks, Price & Rank (October 2026)

GPT-6 Astra by OpenAI ranks 1st of 354 ranked models on the Noometry Index as of October 2026, with a score of 70.8. Its strongest category is knowledge, where it ranks 1st. API pricing starts at $10 per million input tokens and $50 per million output tokens, with a 1.05M-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #1 of 354
- **Index score:** 70.8
- **Evidence:** Confirmed 56 results
- **Provider:** [OpenAI](https://noometry.com/providers/openai)
- **Released:** September 3, 2026
- **Weights:** Proprietary
- **Reasoning:** Yes
- **Context window:** 1.05M
- **Max output:** 128K
- **Input price:** $10 / M
- **Output price:** $50 / M
- **Blended price:** $20 / M
- **Output speed:** Not measured
- **Value:** #206 of 219
- **Knowledge cutoff:** April 2026
- **Input:** text, image, pdf

## Category scores

Each category score combines every public result we have in that category.

GPT-6 Astra category scores

1.  Coding 73.7
2.  Agentic & Tool Use 52.9
3.  Reasoning 85.1
4.  Math 93.5
5.  Knowledge 75.3
6.  Multimodal 55.0
7.  Multilingual 53.7
8.  Instruction Following 76.3
9.  Long Context 44.5
10.  Writing & Preference 75.3
11.  050100

GPT-6 Astra category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 73.7 | #2 | 9 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 52.9 | #3 | 4 |
| [Reasoning](https://noometry.com/best/reasoning) | 85.1 | #1 | 10 |
| [Math](https://noometry.com/best/math) | 93.5 | #2 | 5 |
| [Knowledge](https://noometry.com/best/knowledge) | 75.3 | #1 | 5 |
| [Multimodal](https://noometry.com/best/multimodal) | 55.0 | #3 | 3 |
| [Multilingual](https://noometry.com/best/multilingual) | 53.7 | #61 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 76.3 | #44 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 44.5 | #62 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 75.3 | #7 | 4 |

## Strengths and weaknesses

Categories where GPT-6 Astra places highest and lowest among the models ranked in each, with its score against that category's median.

### Strongest categories

GPT-6 Astra: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Reasoning](https://noometry.com/best/reasoning) | 85.1 | +61.5 | #1 of 350, top 1% |
| [Knowledge](https://noometry.com/best/knowledge) | 75.3 | +38.0 | #1 of 314, top 1% |
| [Coding](https://noometry.com/best/coding) | 73.7 | +35.0 | #2 of 340, top 1% |

### Weakest categories

GPT-6 Astra: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Long Context](https://noometry.com/best/long-context) | 44.5 | +3.6 | #62 of 296, top 21% |
| [Multilingual](https://noometry.com/best/multilingual) | 53.7 | +6.3 | #61 of 297, top 21% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 76.3 | +5.0 | #44 of 305, top 15% |

## Closest competitors

The models ranked just above and below GPT-6 Astra. When scores are this close, price and speed are often the better way to choose.

Models ranked closest to GPT-6 Astra
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [Claude Fable 5.1](https://noometry.com/models/claude-fable-5-1) | #2 | 69.0 | $20 | — | [Compare](https://noometry.com/compare/claude-fable-5-1-vs-gpt-6-astra) |
| [Claude Opus 5.5](https://noometry.com/models/claude-opus-5-5) | #3 | 68.6 | $8 | — | [Compare](https://noometry.com/compare/claude-opus-5-5-vs-gpt-6-astra) |
| [Claude Opus 5](https://noometry.com/models/claude-opus-5) | #4 | 67.8 | $10 | — | [Compare](https://noometry.com/compare/claude-opus-5-vs-gpt-6-astra) |
| [Claude Fable 5](https://noometry.com/models/claude-fable-5) | #5 | 66.8 | $20 | 25 | [Compare](https://noometry.com/compare/claude-fable-5-vs-gpt-6-astra) |
| [GPT-6.1 Sol](https://noometry.com/models/gpt-6-1-sol) | #6 | 65.6 | $4 | — | [Compare](https://noometry.com/compare/gpt-6-1-sol-vs-gpt-6-astra) |
| [GPT-5.6 Sol](https://noometry.com/models/gpt-5-6-sol) | #7 | 65.0 | $8 | 10 | [Compare](https://noometry.com/compare/gpt-5-6-sol-vs-gpt-6-astra) |
| [GPT-5.5 Pro](https://noometry.com/models/gpt-5-5-pro) | #8 | 64.3 | $67.50 | — | [Compare](https://noometry.com/compare/gpt-5-5-pro-vs-gpt-6-astra) |
| [GPT-5.5](https://noometry.com/models/gpt-5-5) | #9 | 63.4 | $11.25 | 25 | [Compare](https://noometry.com/compare/gpt-5-5-vs-gpt-6-astra) |

Sponsored placements are available on pages like this one. [Advertise on Noometry](https://noometry.com/advertise)

## Benchmark results

Every published result we track, with its source. Bold rows are the ones used for ranking; where several exist we prefer independent runs over self-reported numbers.

### Coding

GPT-6 Astra Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 73.2% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 67% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 73.2% |  | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 72.8% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 74.1% | #2 of 29, top 7% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 53.3% | #4 of 37, top 11% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1786 | #2 of 113, top 2% |  | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [FrontierSWE](https://noometry.com/benchmarks/frontierswe) | 65.5% | Best of 18 | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 55.4% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 54.1% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 56.5% | #19 of 121, top 16% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 54.2% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 53.5% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 55.7% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GSO](https://noometry.com/benchmarks/gso-bench) | 79.4% | #2 of 31, top 7% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 92.9% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 93.3% |  | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [WeirdML](https://noometry.com/benchmarks/weirdml) | 93.6% | Best of 119 | promax | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1487 | #35 of 294, top 12% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [MirrorCode](https://noometry.com/benchmarks/mirrorcode) | 46.7% | #4 of 9, top 45% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 2,951 | Best of 105 | max | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

GPT-6 Astra Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [APEX-Agents](https://noometry.com/benchmarks/apex-agents) | 64.7% | #8 of 49, top 17% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Remote Labor Index](https://noometry.com/benchmarks/remote-labor-index) | 20.8% | Best of 14 |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [BALROG](https://noometry.com/benchmarks/balrog) | 68.3% | Best of 35 | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 34.2% | Best of 36 | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Vending-Bench 2](https://noometry.com/benchmarks/vending-bench-2) | 15,515 | Best of 60 |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

GPT-6 Astra Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 92.1% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 85.4% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 95% | Best of 83 | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 92.1% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 59.6% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 93.3% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 98.1% | Best of 91 | xhigh reasoning | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 98.5% | #5 of 83, top 7% | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 96.5% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 97.5% |  | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 97.5% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 86% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 98.5% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 28.9% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 26.3% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 31.7% | #4 of 134, top 3% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 29.1% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 19.7% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 31.4% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Chess Puzzles](https://noometry.com/benchmarks/chess-puzzles) | 72% | Best of 129 | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [EBR-Bench](https://noometry.com/benchmarks/ebr-bench) | 76.2% | Best of 24 | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1462 | #44 of 297, top 15% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 84% | Best of 74 | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 97.1% |  |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 96.5% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 94.9% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 97.1% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 97.3% | #5 of 151, top 4% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 64.1% |  |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 63.8% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 62.2% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 62.9% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 64.4% | #4 of 125, top 4% | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Bench to the Future 3](https://noometry.com/benchmarks/btf-3) | 0.14 | #8 of 10, top 80% | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 166.45 | #2 of 213, top 1% |  | [Epoch AI](https://epoch.ai/eci) | 2026-09-03 |

### Math

GPT-6 Astra Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 93.7% | #2 of 81, top 3% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 97.6% | #2 of 63, top 4% | high | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 87.8% |  | low | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 97.6% |  | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 97.6% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 82.9% |  | none | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 97.6% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 100% | #9 of 173, top 6% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [ProofBench](https://noometry.com/benchmarks/proofbench) | 99% | #7 of 77, top 10% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1465 | #46 of 285, top 17% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [FrontierMath Erdős](https://noometry.com/benchmarks/frontiermath-erdos) | 2.9% | Best of 7 | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-28 |

### Knowledge

GPT-6 Astra Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 95.8% | Best of 186 | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [Humanity's Last Exam](https://noometry.com/benchmarks/hle) | 54.8% | Best of 41 |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SimpleQA Verified](https://noometry.com/benchmarks/simpleqa-verified) | 75.6% | Best of 77 | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-08-30 |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 8.7% | #41 of 96, top 43% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1483 | #38 of 273, top 14% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

GPT-6 Astra Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1281 | #29 of 122, top 24% |  | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |
| [Blueprint-Bench 2](https://noometry.com/benchmarks/blueprint-bench-2) | 49.7% | #3 of 31, top 10% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Furniture Assembly](https://noometry.com/benchmarks/furniture-assembly) | 80% | #3 of 31, top 10% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-10 |
| [LMArena Document](https://noometry.com/benchmarks/arena-document) | 1468 | #13 of 38, top 35% |  | [LMArena](https://lmarena.ai/leaderboard/document) | 2026-09-13 |

### Multilingual

GPT-6 Astra Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1430 | #61 of 297, top 21% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1484 | #61 of 285, top 22% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1456 | #56 of 223, top 26% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1440 | #56 of 231, top 25% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1379 | #79 of 211, top 38% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1426 | #32 of 213, top 16% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1436 | #57 of 283, top 21% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1407 | #103 of 226, top 46% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

GPT-6 Astra Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1450 | #42 of 298, top 15% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

GPT-6 Astra Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1456 | #44 of 291, top 16% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

GPT-6 Astra Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1441 | #61 of 297, top 21% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1418 | #55 of 295, top 19% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [EQ-Bench Creative Writing](https://noometry.com/benchmarks/eqbench-creative-writing) | 2173 | Best of 115 |  | [EQ-Bench](https://eqbench.com/creative_writing.html) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1448 | #58 of 295, top 20% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

GPT-6 Astra API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [azure](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models) | $10 | $50 | $1 | 2026-10-10 |
| [bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html) | $10 | $50 | $1 | 2026-10-10 |
| [openai](https://platform.openai.com/docs/models) | $10 | $50 | $1 | 2026-10-10 |
| [openrouter](https://openrouter.ai/openai/gpt-6-astra) | $10 | $50 | $1 | 2026-10-10 |

[All OpenAI API prices →](https://noometry.com/llm-pricing/openai) [Estimate your cost →](https://noometry.com/tools/cost-calculator)

## Compare GPT-6 Astra

-   [GPT-6 Astra vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-gpt-6-astra)
-   [GPT-6 Astra vs Claude Opus 5.5](https://noometry.com/compare/claude-opus-5-5-vs-gpt-6-astra)
-   [GPT-6 Astra vs Claude Opus 5](https://noometry.com/compare/claude-opus-5-vs-gpt-6-astra)
-   [GPT-6 Astra vs Claude Fable 5](https://noometry.com/compare/claude-fable-5-vs-gpt-6-astra)
-   [GPT-6 Astra vs GPT-6.1 Sol](https://noometry.com/compare/gpt-6-1-sol-vs-gpt-6-astra)
-   [GPT-6 Astra vs GPT-5.6 Sol](https://noometry.com/compare/gpt-5-6-sol-vs-gpt-6-astra)
-   [GPT-6 Astra vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-gpt-6-astra)
-   [GPT-6 Astra vs Kimi K3](https://noometry.com/compare/gpt-6-astra-vs-kimi-k3)
-   [GPT-6 Astra vs Grok 4.6](https://noometry.com/compare/gpt-6-astra-vs-grok-4-6)
-   [GPT-6 Astra vs Qwen3.8 Max](https://noometry.com/compare/gpt-6-astra-vs-qwen3-8-max)
-   [GPT-6 Astra vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-gpt-6-astra)
-   [GPT-6 Astra vs Muse Spark 1.3](https://noometry.com/compare/gpt-6-astra-vs-muse-spark-1-3)
-   [GPT-6 Astra vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-gpt-6-astra)
-   [GPT-6 Astra vs MiMo-V2.6-Pro](https://noometry.com/compare/gpt-6-astra-vs-mimo-v2-6-pro)

## Other OpenAI models

-   [GPT-6.1 Sol](https://noometry.com/models/gpt-6-1-sol)65.6
-   [GPT-5.6 Sol](https://noometry.com/models/gpt-5-6-sol)65.0
-   [GPT-5.5 Pro](https://noometry.com/models/gpt-5-5-pro)64.3
-   [GPT-5.5](https://noometry.com/models/gpt-5-5)63.4
-   [GPT-6 Sol](https://noometry.com/models/gpt-6-sol)61.8
-   [GPT-5.4](https://noometry.com/models/gpt-5-4)59.4
-   [GPT-5.6 Terra](https://noometry.com/models/gpt-5-6-terra)59.2
-   [GPT-5.4 Pro](https://noometry.com/models/gpt-5-4-pro)58.9

## Frequently asked questions

### How good is GPT-6 Astra?

GPT-6 Astra by OpenAI ranks 1st of 354 ranked models on the Noometry Index as of October 2026, with a score of 70.8. Its strongest category is knowledge, where it ranks 1st. API pricing starts at $10 per million input tokens and $50 per million output tokens, with a 1.05M-token context window.

### How much does GPT-6 Astra cost?

GPT-6 Astra costs $10 per million input tokens and $50 per million output tokens on OpenAI's own API, with cached input at $1.

### What is GPT-6 Astra's context window?

GPT-6 Astra accepts up to 1.05M tokens of input and can write up to 128K tokens in one response.

### Is GPT-6 Astra open source?

No. GPT-6 Astra is proprietary and available only through OpenAI's API and partner platforms.

### What are GPT-6 Astra's strengths and weaknesses?

Relative to other ranked models, GPT-6 Astra places best in reasoning, knowledge, coding and lowest in long context, multilingual, instruction following.

### What is GPT-6 Astra best at?

Its best category is knowledge, where it ranks 1st on Noometry.

### Cite this page

Noometry. (2026). GPT-6 Astra benchmarks and pricing. Retrieved October 10, 2026, from https://noometry.com/models/gpt-6-astra

Quote Noometry with a link back to this page. It is also available in [Markdown](https://noometry.com/md/models/gpt-6-astra.md).