OpenAI, proprietary
GPT-5.6 Sol
GPT-5.6 Sol by OpenAI ranks 7th of 354 ranked models on the Noometry Index as of October 2026, with a score of 65.0. Its strongest category is agentic & tool use, where it ranks 7th. API pricing starts at $4 per million input tokens and $20 per million output tokens, with a 1.05M-token context window.
Last verified
Specifications
- Noometry rank
- #7 of 354
- Index score
- 65.0
- Evidence
- Confirmed 65 results
- Provider
- OpenAI
- Released
- July 9, 2026
- Weights
- Proprietary
- Reasoning
- Yes
- Context window
- 1.05M
- Max output
- 128K
- Input price
- $4 / M
- Output price
- $20 / M
- Blended price
- $8 / M
- Output speed
- 10 tokens/s Kagi
- Value
- #193 of 219
- Knowledge cutoff
- February 2026
- Input
- text, image, pdf
Category scores
Each category score combines every public result we have in that category.
- Coding 65.1
- Agentic & Tool Use 50.3
- Reasoning 74.8
- Math 85.6
- Knowledge 64.3
- Multimodal 48.6
- Multilingual 55.3
- Instruction Following 77.7
- Long Context 45.4
- Writing & Preference 73.3
| Category | Score | Rank | Results |
|---|---|---|---|
| Coding | 65.1 | #7 | 10 |
| Agentic & Tool Use | 50.3 | #7 | 7 |
| Reasoning | 74.8 | #8 | 14 |
| Math | 85.6 | #9 | 5 |
| Knowledge | 64.3 | #18 | 4 |
| Multimodal | 48.6 | #9 | 3 |
| Multilingual | 55.3 | #32 | 1 |
| Instruction Following | 77.7 | #16 | 1 |
| Long Context | 45.4 | #42 | 1 |
| Writing & Preference | 73.3 | #12 | 5 |
Strengths and weaknesses
Categories where GPT-5.6 Sol places highest and lowest among the models ranked in each, with its score against that category's median.
Strongest categories
Weakest categories
| Category | Score | vs median | Rank |
|---|---|---|---|
| Long Context | 45.4 | +4.4 | #42 of 296, top 15% |
| Multilingual | 55.3 | +7.9 | #32 of 297, top 11% |
| Multimodal | 48.6 | +10.1 | #9 of 128, top 8% |
Closest competitors
The models ranked just above and below GPT-5.6 Sol. When scores are this close, price and speed are often the better way to choose.
| Model | Rank | Score | Blended $/M | Speed | |
|---|---|---|---|---|---|
| Claude Opus 5.5 | #3 | 68.6 | $8 | — | Compare |
| Claude Opus 5 | #4 | 67.8 | $10 | — | Compare |
| Claude Fable 5 | #5 | 66.8 | $20 | 25 | Compare |
| GPT-6.1 Sol | #6 | 65.6 | $4 | — | Compare |
| GPT-5.5 Pro | #8 | 64.3 | $67.50 | — | Compare |
| GPT-5.5 | #9 | 63.4 | $11.25 | 25 | Compare |
| Claude Sonnet 5.5 | #10 | 61.9 | $4 | — | Compare |
| Gemini 3.8 Flash | #11 | 61.8 | $1.50 | — | Compare |
Sponsored placements are available on pages like this one. Advertise on Noometry
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
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| DeepSWE | 69.4% | high | Epoch AI | ||
| DeepSWE | 45.4% | low | Epoch AI | ||
| DeepSWE | 72.7% | #5 of 29, top 18% | max | Epoch AI | |
| DeepSWE | 61.1% | medium | Epoch AI | ||
| DeepSWE | 70.7% | xhigh | Epoch AI | ||
| FrontierCode | 47.5% | #11 of 37, top 30% | Epoch AI | ||
| CursorBench | 35.7% | high | Epoch AI | ||
| CursorBench | 24.6% | low | Epoch AI | ||
| CursorBench | 41.7% | #7 of 14, top 50% | max | Epoch AI | |
| CursorBench | 31.1% | medium | Epoch AI | ||
| CursorBench | 37.7% | xhigh | Epoch AI | ||
| LMArena WebDev | 1618 | #19 of 113, top 17% | LMArena | 2026-10-08 | |
| FrontierSWE | 32.2% | #8 of 18, top 45% | max | Epoch AI | |
| SciCode | 56.9% | high | Epoch AI | ||
| SciCode | 55.4% | low | Epoch AI | ||
| SciCode | 57.1% | #16 of 121, top 14% | max | Epoch AI | |
| SciCode | 56.5% | medium | Epoch AI | ||
| SciCode | 47.1% | none | Epoch AI | ||
| SciCode | 56% | xhigh | Epoch AI | ||
| GSO | 76.5% | #4 of 31, top 13% | Epoch AI | ||
| WeirdML | 88.8% | high | Epoch AI | ||
| WeirdML | 87% | max | Epoch AI | ||
| WeirdML | 89.4% | #5 of 119, top 5% | promax | Epoch AI | |
| LMArena Coding | 1498 | #21 of 294, top 8% | xhigh | LMArena | 2026-10-08 |
| MirrorCode | 20% | #6 of 9, top 67% | high | Epoch AI | 2026-08-10 |
| ALE-Bench | 2,177 | #3 of 105, top 3% | max | Epoch AI |
Agentic & Tool Use
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| APEX-Agents | 51.4% | #24 of 49, top 49% | promax | Epoch AI | |
| OSWorld 2.0 | 27.3% | #2 of 9, top 23% | max | Epoch AI | |
| τ²-bench Banking | 46.9% | #4 of 26, top 16% | xhigh | τ²-bench | 2026-08-04 |
| PostTrainBench | 36.2% | #2 of 11, top 19% | max | Epoch AI | |
| BALROG | 60% | #3 of 35, top 9% | max | Epoch AI | |
| GBAEval | 52.6% | #7 of 23, top 31% | Epoch AI | ||
| GDP.pdf | 30.7% | #3 of 36, top 9% | Epoch AI | ||
| GDP.pdf | 30.7% | max | Epoch AI | ||
| LMArena Search | 1257 | Best of 32 | xhigh | LMArena | 2026-08-24 |
| Vending-Bench 2 | 9,619 | #7 of 60, top 12% | Epoch AI |
Reasoning
Math
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| FrontierMath (Tiers 1-3) | 89.1% | #6 of 81, top 8% | max | Epoch AI | 2026-07-09 |
| FrontierMath Tier 4 | 82.9% | #7 of 63, top 12% | max | Epoch AI | 2026-07-09 |
| FrontierMath Tier 4 | 80.5% | promax | Epoch AI | 2026-07-09 | |
| OTIS Mock AIME 2024-2025 | 95.6% | low | Epoch AI | 2026-08-07 | |
| OTIS Mock AIME 2024-2025 | 100% | #7 of 173, top 5% | max | Epoch AI | 2026-07-09 |
| OTIS Mock AIME 2024-2025 | 68.9% | none | Epoch AI | 2026-08-07 | |
| ProofBench | 83% | #10 of 77, top 13% | max | Epoch AI | |
| LMArena Math | 1474 | #35 of 285, top 13% | xhigh | LMArena | 2026-10-08 |
| FrontierMath Erdős | 0% | #7 of 7, top 100% | max | Epoch AI | 2026-08-28 |
Knowledge
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| GPQA Diamond | 89.9% | low | Epoch AI | 2026-08-07 | |
| GPQA Diamond | 93.5% | #14 of 186, top 8% | max | Epoch AI | 2026-07-09 |
| GPQA Diamond | 82.8% | none | Epoch AI | 2026-08-07 | |
| SimpleQA Verified | 69.7% | #8 of 77, top 11% | max | Epoch AI | 2026-08-10 |
| Vectara Hallucination Rate (lower is better) | 12.4% | #78 of 96, top 82% | Vectara Hallucination Leaderboard | ||
| LMArena Expert | 1516 | #12 of 273, top 5% | xhigh | LMArena | 2026-10-08 |
Multimodal
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Vision | 1281 | #28 of 122, top 23% | xhigh | LMArena | 2026-10-09 |
| Blueprint-Bench 2 | 33.6% | #10 of 31, top 33% | Epoch AI | ||
| Furniture Assembly | 56.7% | #8 of 31, top 26% | max | Epoch AI | 2026-09-10 |
| LMArena Document | 1483 | #7 of 38, top 19% | xhigh | LMArena | 2026-09-13 |
Multilingual
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Non-English | 1452 | #31 of 297, top 11% | xhigh | LMArena | 2026-10-08 |
| LMArena Chinese | 1527 | #21 of 285, top 8% | xhigh | LMArena | 2026-10-08 |
| LMArena French | 1477 | #29 of 223, top 14% | xhigh | LMArena | 2026-10-08 |
| LMArena German | 1476 | #22 of 231, top 10% | xhigh | LMArena | 2026-10-08 |
| LMArena Japanese | 1471 | #18 of 211, top 9% | xhigh | LMArena | 2026-10-08 |
| LMArena Korean | 1442 | #24 of 213, top 12% | xhigh | LMArena | 2026-10-08 |
| LMArena Russian | 1468 | #28 of 283, top 10% | xhigh | LMArena | 2026-10-08 |
| LMArena Spanish | 1441 | #64 of 226, top 29% | xhigh | LMArena | 2026-10-08 |
Instruction Following
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Instruction Following | 1482 | #13 of 298, top 5% | xhigh | LMArena | 2026-10-08 |
Long Context
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Longer Query | 1480 | #23 of 291, top 8% | xhigh | LMArena | 2026-10-08 |
Writing & Preference
| Benchmark | Score | Position | Setting | Source | Date |
|---|---|---|---|---|---|
| LMArena Text | 1457 | #37 of 297, top 13% | xhigh | LMArena | 2026-10-08 |
| LMArena Creative Writing | 1448 | #30 of 295, top 11% | xhigh | LMArena | 2026-10-08 |
| EQ-Bench Creative Writing | 1972 | #9 of 115, top 8% | EQ-Bench | ||
| EQ-Bench 4 | 1250 | #9 of 28, top 33% | EQ-Bench | ||
| LMArena Multi-Turn | 1460 | #38 of 295, top 13% | xhigh | LMArena | 2026-10-08 |
API pricing by provider
| Route | Input $/M | Output $/M | Cached input $/M | Checked |
|---|---|---|---|---|
| azure | $4 | $20 | $0.50 | 2026-10-10 |
| bedrock | $4 | $20 | $0.40 | 2026-10-10 |
| openai | $4 | $20 | $0.40 | 2026-10-10 |
| openrouter | $2 | $10 | $0.20 | 2026-10-10 |
Compare GPT-5.6 Sol
- GPT-5.6 Sol vs GPT-6.1 Sol
- GPT-5.6 Sol vs GPT-5.5 Pro
- GPT-5.6 Sol vs Claude Fable 5
- GPT-5.6 Sol vs GPT-5.5
- GPT-5.6 Sol vs Claude Opus 5
- GPT-5.6 Sol vs Claude Sonnet 5.5
- GPT-5.6 Sol vs Claude Fable 5.1
- GPT-5.6 Sol vs Gemini 3.8 Flash
- GPT-5.6 Sol vs Kimi K3
- GPT-5.6 Sol vs Grok 4.6
- GPT-5.6 Sol vs Qwen3.8 Max
- GPT-5.6 Sol vs GLM-5.3
- GPT-5.6 Sol vs Muse Spark 1.3
- GPT-5.6 Sol vs DeepSeek V4 Pro
Other OpenAI models
- GPT-6 Astra70.8
- GPT-6.1 Sol65.6
- GPT-5.5 Pro64.3
- GPT-5.563.4
- GPT-6 Sol61.8
- GPT-5.459.4
- GPT-5.6 Terra59.2
- GPT-5.4 Pro58.9
Frequently asked questions
How good is GPT-5.6 Sol?
GPT-5.6 Sol by OpenAI ranks 7th of 354 ranked models on the Noometry Index as of October 2026, with a score of 65.0. Its strongest category is agentic & tool use, where it ranks 7th. API pricing starts at $4 per million input tokens and $20 per million output tokens, with a 1.05M-token context window.
How much does GPT-5.6 Sol cost?
GPT-5.6 Sol costs $4 per million input tokens and $20 per million output tokens on OpenAI's own API, with cached input at $0.40.
What is GPT-5.6 Sol's context window?
GPT-5.6 Sol accepts up to 1.05M tokens of input and can write up to 128K tokens in one response.
Is GPT-5.6 Sol open source?
No. GPT-5.6 Sol is proprietary and available only through OpenAI's API and partner platforms.
How fast is GPT-5.6 Sol?
GPT-5.6 Sol generated about 10 output tokens per second in the Kagi LLM Benchmark's timed runs. Speed varies by provider, load and reasoning effort.
What are GPT-5.6 Sol's strengths and weaknesses?
Relative to other ranked models, GPT-5.6 Sol places best in coding, reasoning, math and lowest in long context, multilingual, multimodal.
What is GPT-5.6 Sol best at?
Its best category is agentic & tool use, where it ranks 7th on Noometry.