OpenAI, proprietary

# GPT-6 Sol

> GPT-6 Sol by OpenAI, released September 2026. Ranked #12 of 354 with a Noometry Index of 61.8. API: $2 in / $10 out per M tokens. 1.05M context. Scores, sources and comparisons.
- Canonical page: https://noometry.com/models/gpt-6-sol
- Last updated: 2026-10-10
- Title: GPT-6 Sol Benchmarks, Price & Rank (October 2026) | Noometry

GPT-6 Sol by OpenAI ranks 12th of 354 ranked models on the Noometry Index as of October 2026, with a score of 61.8. Its strongest category is math, where it ranks 7th. API pricing starts at $2 per million input tokens and $10 per million output tokens, with a 1.05M-token context window.

Last verified October 10, 2026

## Specifications

- **Noometry rank:** #12 of 354
- **Index score:** 61.8
- **Evidence:** Confirmed 45 results
- **Provider:** [OpenAI](https://noometry.com/providers/openai)
- **Released:** September 22, 2026
- **Weights:** Proprietary
- **Reasoning:** Yes
- **Context window:** 1.05M
- **Max output:** 128K
- **Input price:** $2 / M
- **Output price:** $10 / M
- **Blended price:** $4 / M
- **Output speed:** Not measured
- **Value:** #163 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 Sol category scores

1.  Coding 60.1
2.  Agentic & Tool Use 37.2
3.  Reasoning 74.0
4.  Math 87.2
5.  Knowledge 64.8
6.  Multimodal 47.6
7.  Multilingual 50.5
8.  Instruction Following 74.5
9.  Long Context 43.1
10.  Writing & Preference 71.9
11.  050100

GPT-6 Sol category ranks
| Category | Score | Rank | Results |
| --- | --- | --- | --- |
| [Coding](https://noometry.com/best/coding) | 60.1 | #11 | 5 |
| [Agentic & Tool Use](https://noometry.com/best/agentic) | 37.2 | #36 | 2 |
| [Reasoning](https://noometry.com/best/reasoning) | 74.0 | #9 | 9 |
| [Math](https://noometry.com/best/math) | 87.2 | #7 | 5 |
| [Knowledge](https://noometry.com/best/knowledge) | 64.8 | #15 | 4 |
| [Multimodal](https://noometry.com/best/multimodal) | 47.6 | #10 | 3 |
| [Multilingual](https://noometry.com/best/multilingual) | 50.5 | #118 | 1 |
| [Instruction Following](https://noometry.com/best/instruction-following) | 74.5 | #94 | 1 |
| [Long Context](https://noometry.com/best/long-context) | 43.1 | #108 | 1 |
| [Writing & Preference](https://noometry.com/best/writing) | 71.9 | #18 | 4 |

## Strengths and weaknesses

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

### Strongest categories

GPT-6 Sol: strongest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Math](https://noometry.com/best/math) | 87.2 | +50.7 | #7 of 327, top 3% |
| [Reasoning](https://noometry.com/best/reasoning) | 74.0 | +50.4 | #9 of 350, top 3% |
| [Coding](https://noometry.com/best/coding) | 60.1 | +21.4 | #11 of 340, top 4% |

### Weakest categories

GPT-6 Sol: weakest categories
| Category | Score | vs median | Rank |
| --- | --- | --- | --- |
| [Multilingual](https://noometry.com/best/multilingual) | 50.5 | +3.1 | #118 of 297, top 40% |
| [Long Context](https://noometry.com/best/long-context) | 43.1 | +2.1 | #108 of 296, top 37% |
| [Instruction Following](https://noometry.com/best/instruction-following) | 74.5 | +3.2 | #94 of 305, top 31% |

## Closest competitors

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

Models ranked closest to GPT-6 Sol
| Model | Rank | Score | Blended $/M | Speed |  |
| --- | --- | --- | --- | --- | --- |
| [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-sol) |
| [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-sol) |
| [Claude Sonnet 5.5](https://noometry.com/models/claude-sonnet-5-5) | #10 | 61.9 | $4 | — | [Compare](https://noometry.com/compare/claude-sonnet-5-5-vs-gpt-6-sol) |
| [Gemini 3.8 Flash](https://noometry.com/models/gemini-3-8-flash) | #11 | 61.8 | $1.50 | — | [Compare](https://noometry.com/compare/gemini-3-8-flash-vs-gpt-6-sol) |
| [Claude Opus 4.8](https://noometry.com/models/claude-opus-4-8) | #13 | 60.7 | $10 | 34 | [Compare](https://noometry.com/compare/claude-opus-4-8-vs-gpt-6-sol) |
| [Gemini 3.7 Flash](https://noometry.com/models/gemini-3-7-flash) | #14 | 59.8 | $1.50 | — | [Compare](https://noometry.com/compare/gemini-3-7-flash-vs-gpt-6-sol) |
| [Kimi K3](https://noometry.com/models/kimi-k3) | #15 | 59.5 | $6 | — | [Compare](https://noometry.com/compare/gpt-6-sol-vs-kimi-k3) |
| [GPT-5.4](https://noometry.com/models/gpt-5-4) | #16 | 59.4 | $5.63 | 12 | [Compare](https://noometry.com/compare/gpt-5-4-vs-gpt-6-sol) |

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 Sol Coding benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 65.3% |  | high | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 37.2% |  | low | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 68.8% | #9 of 29, top 32% | max | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 56.6% |  | medium | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [DeepSWE](https://noometry.com/benchmarks/deepswe) | 66.6% |  | xhigh | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 49.3% | #8 of 37, top 22% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 47.7% |  | high | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 37.3% |  | low | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 49.3% |  | max | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 45.9% |  | medium | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [FrontierCode](https://noometry.com/benchmarks/frontiercode) | 48.4% |  | xhigh | [Model card](https://openai.com/index/introducing-gpt-6-sol-and-luna/) (self-reported) | 2026-09-22 |
| [LMArena WebDev](https://noometry.com/benchmarks/arena-webdev) | 1688 | #7 of 113, top 7% |  | [LMArena](https://lmarena.ai/leaderboard/webdev) | 2026-10-08 |
| [SciCode](https://noometry.com/benchmarks/scicode) | 54.9% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 50.2% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 57.6% | #15 of 121, top 13% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 53.8% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 47.3% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [SciCode](https://noometry.com/benchmarks/scicode) | 55.1% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Coding](https://noometry.com/benchmarks/arena-coding) | 1447 | #89 of 294, top 31% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [ALE-Bench](https://noometry.com/benchmarks/ale-bench) | 2,462 | #2 of 105, top 2% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Agentic & Tool Use

GPT-6 Sol Agentic & Tool Use benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [APEX-Agents](https://noometry.com/benchmarks/apex-agents) | 54.3% | #21 of 49, top 43% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 26.4% | #8 of 36, top 23% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 28% |  | high | [Model card](https://openai.com/index/introducing-gpt-6-1-sol/) (self-reported) | 2026-09-29 |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 21.8% |  | low | [Model card](https://openai.com/index/introducing-gpt-6-1-sol/) (self-reported) | 2026-09-29 |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 24.8% |  | max | [Model card](https://openai.com/index/introducing-gpt-6-1-sol/) (self-reported) | 2026-09-29 |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 25.4% |  | medium | [Model card](https://openai.com/index/introducing-gpt-6-1-sol/) (self-reported) | 2026-09-29 |
| [GDP.pdf](https://noometry.com/benchmarks/gdp-pdf) | 23.8% |  | xhigh | [Model card](https://openai.com/index/introducing-gpt-6-1-sol/) (self-reported) | 2026-09-29 |
| [Vending-Bench 2](https://noometry.com/benchmarks/vending-bench-2) | 14,428 | #2 of 60, top 4% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |

### Reasoning

GPT-6 Sol Reasoning benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 68.9% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 31.5% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 89.6% | #7 of 83, top 9% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 57.8% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 1.7% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-2](https://noometry.com/benchmarks/arc-agi-2) | 78.1% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [NYT Connections (extended)](https://noometry.com/benchmarks/nyt-connections) | 90.1% | #17 of 91, top 19% | high reasoning | [Lech Mazur benchmarks](https://github.com/lechmazur/nyt-connections) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 91% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 72.2% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 95.5% | #14 of 83, top 17% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 83.7% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 29.3% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [ARC-AGI-1](https://noometry.com/benchmarks/arc-agi-1) | 92.7% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 25.4% |  | high | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 16.3% |  | low | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 30.9% | #7 of 134, top 6% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 24.6% |  | medium | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 4% |  | none | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [CritPt](https://noometry.com/benchmarks/critpt) | 28% |  | xhigh | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [EBR-Bench](https://noometry.com/benchmarks/ebr-bench) | 53.3% | #5 of 24, top 21% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-22 |
| [LMArena Hard Prompts](https://noometry.com/benchmarks/arena-hard-prompts) | 1418 | #107 of 297, top 37% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [Mystery Game Puzzles](https://noometry.com/benchmarks/mystery-game-puzzles) | 56% | #9 of 74, top 13% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-22 |
| [DTBench](https://noometry.com/benchmarks/dtbench) | 97.3% | #6 of 151, top 4% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMCA](https://noometry.com/benchmarks/lmca) | 59.1% | #7 of 125, top 6% | max | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Epoch Capabilities Index](https://noometry.com/benchmarks/epoch-capabilities-index) | 162.72 | #7 of 213, top 4% |  | [Epoch AI](https://epoch.ai/eci) | 2026-09-22 |

### Math

GPT-6 Sol Math benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [FrontierMath (Tiers 1-3)](https://noometry.com/benchmarks/frontiermath) | 89.8% | #5 of 81, top 7% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-22 |
| [FrontierMath Tier 4](https://noometry.com/benchmarks/frontiermath-tier-4) | 90% | #5 of 63, top 8% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-22 |
| [OTIS Mock AIME 2024-2025](https://noometry.com/benchmarks/otis-mock-aime) | 100% | #10 of 173, top 6% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-22 |
| [ProofBench](https://noometry.com/benchmarks/proofbench) | 83% | #11 of 77, top 15% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [LMArena Math](https://noometry.com/benchmarks/arena-math) | 1402 | #123 of 285, top 44% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Knowledge

GPT-6 Sol Knowledge benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [GPQA Diamond](https://noometry.com/benchmarks/gpqa-diamond) | 94.3% | #8 of 186, top 5% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-22 |
| [SimpleQA Verified](https://noometry.com/benchmarks/simpleqa-verified) | 60.7% | #14 of 77, top 19% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-22 |
| [Vectara Hallucination Rate](https://noometry.com/benchmarks/vectara-hallucination) (lower is better) | 6.5% | #25 of 96, top 27% |  | [Vectara Hallucination Leaderboard](https://github.com/vectara/hallucination-leaderboard) |  |
| [LMArena Expert](https://noometry.com/benchmarks/arena-expert) | 1439 | #86 of 273, top 32% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Multimodal

GPT-6 Sol Multimodal benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Vision](https://noometry.com/benchmarks/arena-vision) | 1245 | #60 of 122, top 50% |  | [LMArena](https://lmarena.ai/leaderboard/vision) | 2026-10-09 |
| [Blueprint-Bench 2](https://noometry.com/benchmarks/blueprint-bench-2) | 36.9% | #7 of 31, top 23% |  | [Epoch AI](https://epoch.ai/benchmarks) |  |
| [Furniture Assembly](https://noometry.com/benchmarks/furniture-assembly) | 58.3% | #7 of 31, top 23% | max | [Epoch AI](https://epoch.ai/benchmarks) | 2026-09-23 |

### Multilingual

GPT-6 Sol Multilingual benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Non-English](https://noometry.com/benchmarks/arena-non-english) | 1385 | #118 of 297, top 40% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Chinese](https://noometry.com/benchmarks/arena-chinese) | 1405 | #135 of 285, top 48% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena French](https://noometry.com/benchmarks/arena-french) | 1410 | #111 of 223, top 50% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena German](https://noometry.com/benchmarks/arena-german) | 1390 | #103 of 231, top 45% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Japanese](https://noometry.com/benchmarks/arena-japanese) | 1385 | #72 of 211, top 35% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Korean](https://noometry.com/benchmarks/arena-korean) | 1341 | #109 of 213, top 52% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Russian](https://noometry.com/benchmarks/arena-russian) | 1401 | #103 of 283, top 37% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Spanish](https://noometry.com/benchmarks/arena-spanish) | 1384 | #124 of 226, top 55% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Instruction Following

GPT-6 Sol Instruction Following benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Instruction Following](https://noometry.com/benchmarks/arena-instruction-following) | 1412 | #84 of 298, top 29% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Long Context

GPT-6 Sol Long Context benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Longer Query](https://noometry.com/benchmarks/arena-longer-query) | 1411 | #105 of 291, top 37% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

### Writing & Preference

GPT-6 Sol Writing & Preference benchmark results
| Benchmark | Score | Position | Setting | Source | Date |
| --- | --- | --- | --- | --- | --- |
| [LMArena Text](https://noometry.com/benchmarks/arena-text) | 1395 | #124 of 297, top 42% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [LMArena Creative Writing](https://noometry.com/benchmarks/arena-creative-writing) | 1378 | #105 of 295, top 36% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |
| [EQ-Bench Creative Writing](https://noometry.com/benchmarks/eqbench-creative-writing) | 2125 | #4 of 115, top 4% |  | [EQ-Bench](https://eqbench.com/creative_writing.html) |  |
| [LMArena Multi-Turn](https://noometry.com/benchmarks/arena-multi-turn) | 1412 | #105 of 295, top 36% |  | [LMArena](https://lmarena.ai/leaderboard/text) | 2026-10-08 |

## API pricing by provider

GPT-6 Sol API prices
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
| --- | --- | --- | --- | --- |
| [azure](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models) | $2 | $10 | $0.20 | 2026-10-10 |
| [bedrock](https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html) | $2 | $10 | $0.20 | 2026-10-10 |
| [openai](https://platform.openai.com/docs/models) | $2 | $10 | $0.20 | 2026-10-10 |
| [openrouter](https://openrouter.ai/openai/gpt-6-sol) | $2 | $10 | $0.20 | 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 Sol

-   [GPT-6 Sol vs GPT-5.6 Sol](https://noometry.com/compare/gpt-5-6-sol-vs-gpt-6-sol)
-   [GPT-6 Sol vs Gemini 3.8 Flash](https://noometry.com/compare/gemini-3-8-flash-vs-gpt-6-sol)
-   [GPT-6 Sol vs Claude Opus 4.8](https://noometry.com/compare/claude-opus-4-8-vs-gpt-6-sol)
-   [GPT-6 Sol vs Claude Sonnet 5.5](https://noometry.com/compare/claude-sonnet-5-5-vs-gpt-6-sol)
-   [GPT-6 Sol vs Gemini 3.7 Flash](https://noometry.com/compare/gemini-3-7-flash-vs-gpt-6-sol)
-   [GPT-6 Sol vs GPT-5.5](https://noometry.com/compare/gpt-5-5-vs-gpt-6-sol)
-   [GPT-6 Sol vs Kimi K3](https://noometry.com/compare/gpt-6-sol-vs-kimi-k3)
-   [GPT-6 Sol vs Claude Fable 5.1](https://noometry.com/compare/claude-fable-5-1-vs-gpt-6-sol)
-   [GPT-6 Sol vs Grok 4.6](https://noometry.com/compare/gpt-6-sol-vs-grok-4-6)
-   [GPT-6 Sol vs Qwen3.8 Max](https://noometry.com/compare/gpt-6-sol-vs-qwen3-8-max)
-   [GPT-6 Sol vs GLM-5.3](https://noometry.com/compare/glm-5-3-vs-gpt-6-sol)
-   [GPT-6 Sol vs Muse Spark 1.3](https://noometry.com/compare/gpt-6-sol-vs-muse-spark-1-3)
-   [GPT-6 Sol vs DeepSeek V4 Pro](https://noometry.com/compare/deepseek-v4-pro-vs-gpt-6-sol)
-   [GPT-6 Sol vs MiMo-V2.6-Pro](https://noometry.com/compare/gpt-6-sol-vs-mimo-v2-6-pro)

## Other OpenAI models

-   [GPT-6 Astra](https://noometry.com/models/gpt-6-astra)70.8
-   [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-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 Sol?

GPT-6 Sol by OpenAI ranks 12th of 354 ranked models on the Noometry Index as of October 2026, with a score of 61.8. Its strongest category is math, where it ranks 7th. API pricing starts at $2 per million input tokens and $10 per million output tokens, with a 1.05M-token context window.

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

GPT-6 Sol costs $2 per million input tokens and $10 per million output tokens on OpenAI's own API, with cached input at $0.20.

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

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

### Is GPT-6 Sol open source?

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

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

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

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

Its best category is math, where it ranks 7th on Noometry.

### Cite this page

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

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