OpenAIGPT-5.6 Sol
Reasoning effort
GPT-5.6 Sol is an OpenAI proprietary reasoning model, released 9 Jul 2026. Its best configuration (max reasoning effort) ranks #16 of 785 on the BenchLeader Index at 68.0 ±3.7, in the top 25. The ± is the point: 68 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in composite (82) and lowest in knowledge (65). At $8.00 per million tokens blended it is among the most expensive ranked models. Output speed of 86 tokens per second puts it slower than most, with a first answer in 69.5 s. It has been measured at 7 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 20 Oct 2026.
- Blended price
- $8.00/M
- $4.00 in · $20.00 out
- Output speed
- 86 tok/s
- measured by Artificial Analysis
- First answer
- 69 s
- first token 2.42 s
- Context
- 1.1M
- Full answer
- 75 s
- median, reasoning included
- Cost per run
- $1.99
- one full Intelligence Index run
- Released
- 9 Jul 2026
- Overall index68
- Reasoning72
- Coding66
- Agents & tools67
- Maths71
- Knowledge65
- Instruction following71
- Multimodal67
- Long context67
- Composite82
Versions
OpenAI has shipped 3 models under this name. Each is ranked on its own results; a newer version often has fewer results so far, which holds its index nearer the average until more arrive.
| Model | Released | Index | Rank |
|---|---|---|---|
| GPT-6.1 Solmax | 29 Sept 2026 | 69.9 | #7 |
| GPT-6 Solmax | 22 Sept 2026 | 66.4 | #32 |
| GPT-5.6 Solmaxthis page | 9 Jul 2026 | 68.0 | #16 |
Reasoning-effort configurations
The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.
| Effort | Index | Rank | Speed | First answer | Chat reply cost | Categories |
|---|---|---|---|---|---|---|
| no reasoning | 53.7 | #276 | 76 tok/s | 0.91 s | $0.0076 | Agents & tools 48 · Coding 50 · Composite 61 · Knowledge 62 · Long context 56 · Maths 54 · Multimodal 55 · Reasoning 55 |
| low | 62.2 | #88 | 84 tok/s | 1.80 s | $0.0076 | Agents & tools 67 · Coding 63 · Composite 67 · Instruction following 66 · Knowledge 70 · Long context 64 · Maths 65 · Multimodal 64 · Reasoning 57 |
| medium | 64.4 | #52 | 79 tok/s | 3.15 s | $0.0076 | Agents & tools 73 · Coding 64 · Composite 73 · Instruction following 69 · Knowledge 70 · Long context 65 · Multimodal 65 · Reasoning 65 |
| high | 66.3 | #34 | 80 tok/s | 6.01 s | $0.0076 | Agents & tools 73 · Coding 70 · Composite 77 · Instruction following 68 · Knowledge 71 · Long context 66 · Multimodal 65 · Reasoning 68 |
| xhigh | 66.6 | #30 | 82 tok/s | 20 s | $0.0076 | Agents & tools 71 · Coding 65 · Composite 79 · Human preference 68 · Instruction following 70 · Knowledge 71 · Long context 66 · Maths 68 · Multimodal 64 · Reasoning 69 |
| maxbest | 68.0 | #16 | 86 tok/s | 69 s | $0.0076 | Agents & tools 67 · Coding 66 · Composite 82 · Instruction following 71 · Knowledge 65 · Long context 67 · Maths 71 · Multimodal 67 · Reasoning 72 |
| not stated | 55.9 | #218 | 58 tok/s | 2.42 s | $0.0076 | Agents & tools 41 · Coding 71 · Composite 60 · Human preference 58 · Reasoning 62 |
What more thinking costs
Turning the effort up buys index points and multiplies the bill. Here max costs 7.6× low for +5.8 on the index — 2.0 points per doubling of spend. Compare that with other models.
How its index has moved
8 Sept 2026 to 21 Oct 2026- max
- xhigh
- high
- medium
The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.
Benchmark results
See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.
Reasoning
| Benchmark | no reasoning | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|---|
| GPQA Diamond | 82.8%#110 | 89.9%#47 | – | – | – | 93.5%#16 | – | Epoch AI Benchmarking Hub | |
| SimpleBench | – | – | – | – | 64.8%#17 | – | 64.8%#17 | SimpleBench | |
| Arena Hard Prompts | – | – | – | – | 1512#16 | – | – | Arena (LMArena) | |
| LiveBench 2.0 Reasoningnot in indexeffort not stated | – | – | – | – | – | – | 91.7%#5 | LiveBench | |
| LiveBench 1.0 Reasoningnot in index | – | – | – | – | – | 91.7%#5 | – | LiveBench | |
| GPQA Diamond (AA)not in index | 79.0%#203 | 89.8%#68 | 92.6%#32 | 92.8%#28 | 93.1%#24 | 94.1%#7 | – | Artificial Analysis | |
| Humanity's Last Exam (AA)not in index | 16.7%#240 | 39.4%#91 | 42.2%#74 | 46.0%#47 | 47.3%#41 | 49.5%#28 | – | Artificial Analysis | |
| GPQA Diamond (Vals)not in index | – | – | – | – | – | 95.2%#2 | – | Vals AI | |
| EnigmaEval | – | – | – | 37.1%#2 | – | – | – | Scale AI SEAL | |
| Kagi LLM Benchmarkeffort not stated | – | – | – | – | – | – | 67.0%#35 | Kagi LLM Benchmark | |
| ARC-AGI-1 | – | 74.5%#135 | 92.5%#55 | 97.0%#22 | 97.5%#12 | 96.5%#23 | – | ARC Prize | |
| ARC-AGI-2 | – | 42.5%#115 | 67.1%#69 | 85.4%#28 | 90.0%#14 | 92.5%#5 | – | ARC Prize | |
| ARC-AGI-3 | – | 0.3%#53 | 1.1%#40 | 2.2%#35 | 7.0%#26 | 7.8%#25 | – | ARC Prize | |
| CritPt | 5.1%#154 | 14.9%#95 | 22.9%#54 | 25.7%#41 | 28.6%#24 | 32.3%#2 | – | Artificial Analysis | |
| MysteryMechanismnot in index | – | – | – | – | – | 33.3%#12 | – | Vals AI | |
| Chess Puzzlesnot in index | 7.0%#127 | 31.0%#66 | – | – | – | 59.0%#10 | – | Epoch AI Benchmarking Hub | |
| Mystery Game Puzzlesnot in index | 33.0%#28 | 26.0%#43 | – | – | – | 58.0%#7 | – | Epoch AI Benchmarking Hub | |
| LMCAnot in index | 52.8%#53 | 55.9%#43 | 56.4%#42 | 56.9%#40 | 58.5%#37 | 58.4%#38 | – | Epoch AI Benchmarking Hub | |
| DTBenchnot in index | 83.7%#112 | 93.9%#60 | 95.2%#43 | 95.5%#38 | 95.7%#35 | 95.5%#38 | – | Epoch AI Benchmarking Hub | |
| ForecastBenchnot in index | – | – | 66.5%#2 | – | – | 65.5%#11 | – | ForecastBench | |
| BTF-3not in index | – | – | 13.7%#7 | 13.5%#9 | – | 13.7%#7 | – | Epoch AI Benchmarking Hub |
Coding
| Benchmark | no reasoning | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|---|
| SciCode | 47.1%#127 | 56.4%#39 | 57.4%#28 | 57.8%#24 | 57.1%#33 | 57.1%#33 | – | SciCode | |
| WeirdML | – | – | – | 88.8%#10 | – | 87.0%#12 | – | WeirdML | |
| FrontierCodeeffort not stated | – | – | – | – | – | – | 47.5%#13 | Cognition | |
| GSO-Bencheffort not stated | – | – | – | – | – | – | 76.5%#4 | GSO-Bench | |
| Arena Coding | – | – | – | – | 1534#17 | – | – | Arena (LMArena) | |
| Arena WebDev | – | – | – | – | 1615#26 | – | – | Arena (LMArena) | |
| LiveBench 2.0 Codingnot in indexeffort not stated | – | – | – | – | – | – | 89.7%#14 | LiveBench | |
| LiveBench 1.0 Codingnot in index | – | – | – | – | – | 83.9%#7 | – | LiveBench | |
| SciCode (AA)not in index | 47.7%#131 | 56.4%#40 | 57.4%#28 | 57.8%#25 | 57.1%#33 | 57.1%#33 | – | Artificial Analysis | |
| LiveCodeBench | – | – | – | – | – | 82.6%#50 | – | Vals AI | |
| IOI | – | – | – | – | – | 91.2%#5 | – | Vals AI | |
| SWE-bench (Vals)not in index | – | – | – | – | – | 96.2%#3 | – | Vals AI | |
| Code Migrationnot in index | – | – | – | – | – | 52.9%#12 | – | Vals AI | |
| ProgramBenchnot in index | – | – | – | – | – | 1.5%#13 | – | Vals AI | |
| Vibe Code Bench 1-100not in index | – | – | – | – | – | 20.0%#12 | – | Vals AI | |
| Vibe Code Bench v1.1not in index | – | – | – | – | – | 80.5%#25 | – | Vals AI | |
| SWE Atlas: Codebase QnAnot in index | – | – | – | – | 46.0%#7 | – | – | Scale AI SEAL | |
| SWE Atlas: Test Writingnot in index | – | – | – | – | 45.9%#7 | – | – | Scale AI SEAL | |
| MirrorCodenot in index | – | – | – | 20.0%#7 | – | – | – | Epoch AI Benchmarking Hub | |
| Surface Evolver Benchnot in index | – | – | – | – | 93.1%#3 | – | – | Epoch AI Benchmarking Hub | |
| DeepSWE v1.1not in index | – | 45.4%#52 | 61.1%#31 | 69.4%#15 | 70.7%#11 | 72.7%#9 | – | Epoch AI Benchmarking Hub | |
| CursorBenchnot in index | – | 24.6%#74 | 31.1%#62 | 35.7%#51 | 37.7%#43 | 41.7%#32 | – | Cursor | |
| ALE-Benchnot in index | – | – | – | – | – | 2176.9#4 | – | Epoch AI Benchmarking Hub | |
| FrontierSWEnot in index | – | – | – | – | – | 32.2%#9 | – | Epoch AI Benchmarking Hub | |
| Terminal-Bench 4.0 (AA)not in index | – | 1.0%#128 | 14.7%#71 | 20.7%#62 | 24.8%#56 | 39.9%#32 | – | Artificial Analysis | |
| Terminal-Bench 2.1 (AA)not in index | 74.2%#66 | 76.8%#58 | 86.1%#21 | 87.3%#20 | 89.5%#5 | 88.0%#12 | – | Artificial Analysis | |
| Startrise Frontendnot in indexeffort not stated | – | – | – | – | – | – | 66.2%#24 | Startrise |
Agents & tools
| Benchmark | no reasoning | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|---|
| Terminal-Bench | – | – | – | – | – | 37.3%#50 | – | Terminal-Bench | |
| OSWorld-Verified 2.0 | – | – | – | – | – | 27.3%#4 | – | OSWorld | |
| Arena Agent | – | – | – | – | 6.6#10 | – | – | Arena (LMArena) | |
| LiveBench Long Agenticnot in indexeffort not stated | – | – | – | – | – | – | 48.5%#15 | LiveBench | |
| LiveBench Browsernot in indexeffort not stated | – | – | – | – | – | – | 88.0%#7 | LiveBench | |
| LiveBench Agentic Codingnot in index | – | – | – | – | – | 56.2%#29 | – | LiveBench | |
| Terminal-Bench Hard | – | 60.6%#7 | 62.9%#2 | 62.1%#5 | 61.4%#6 | 65.9%#1 | – | Artificial Analysis | |
| τ²-Bench Telecom (AA)not in index | – | 76.0%#134 | 81.0%#119 | 83.3%#110 | 84.8%#97 | 85.1%#94 | – | Artificial Analysis | |
| Terminal-Bench 2.1 (Vals) | – | – | – | – | – | 85.8%#3 | – | Vals AI | |
| HiL-Bencheffort not stated | – | – | – | – | – | – | 32.3%#24 | Scale AI SEAL | |
| τ³-bench Bankingnot in index | – | – | – | – | 46.9%#4 | – | – | τ²-bench | |
| τ³-Banking (AA) | 19.6%#100 | 29.1%#71 | 36.5%#44 | 36.7%#42 | 38.1%#38 | 44.3%#17 | – | Artificial Analysis | |
| ITBench SRE (AA)not in index | – | – | – | – | – | 56.2%#1 | – | Artificial Analysis | |
| Analyst Agent (AA)not in index | – | – | – | – | – | 47.5%#14 | – | Artificial Analysis | |
| CUA-benchnot in index | – | – | – | – | – | 8.3%#5 | – | Vals AI | |
| CyberBenchnot in index | – | – | – | – | – | 76.3%#4 | – | Vals AI | |
| Finance Agent v2not in index | – | – | – | – | – | 53.8%#31 | – | Vals AI | |
| Harvey's Legal Agent Benchmark v1not in index | – | – | – | – | – | 2.5%#45 | – | Vals AI | |
| Legal Research Benchnot in index | – | – | – | – | – | 48.1%#10 | – | Vals AI | |
| SkillsBenchnot in index | – | – | – | – | – | 54.1%#15 | – | Vals AI | |
| SREBenchnot in index | – | – | – | – | – | 30.5%#6 | – | Vals AI | |
| Tax Agent Benchnot in index | – | – | – | – | – | 31.1%#24 | – | Vals AI | |
| Terminal-Bench 4.0 (Vals)not in index | – | – | – | – | – | 37.9%#14 | – | Vals AI | |
| Terminal-Bench Sciencenot in index | – | – | – | – | – | 20.0%#11 | – | Vals AI | |
| Time Horizon Index: KSPnot in index | – | – | – | – | – | 23.8%#5 | – | Vals AI | |
| Web Search Indexnot in index | – | – | – | – | – | 43.6%#5 | – | Vals AI | |
| Arena Searchnot in index | – | – | – | – | 1258#1 | – | – | Arena (LMArena) | |
| BALROGnot in index | – | – | – | – | – | 60.0%#3 | – | BALROG | |
| PostTrainBenchnot in index | – | – | – | – | – | 36.2%#2 | – | Epoch AI Benchmarking Hub | |
| GBAEvalnot in indexeffort not stated | – | – | – | – | – | – | 52.6%#7 | Epoch AI Benchmarking Hub | |
| Vending-Bench 2not in indexeffort not stated | – | – | – | – | – | – | 9619.4#8 | Andon Labs | |
| AutomationBenchnot in index | 22.7%#132 | 41.0%#96 | 51.3%#76 | 55.3%#58 | 55.3%#58 | 60.1%#36 | – | Artificial Analysis | |
| GDP.pdf (AA)not in index | 15.2%#97 | 21.0%#56 | 26.2%#23 | 27.8%#15 | 27.6%#16 | 27.2%#17 | – | Artificial Analysis | |
| EnterpriseOps-Gymnot in index | – | – | – | – | – | 42.9%#20 | – | Artificial Analysis | |
| Terminal-Bench-Science 0.1 (AA)not in index | – | – | – | – | – | 22.4%#20 | – | Artificial Analysis | |
| FACTS Searchnot in indexeffort not stated | – | – | – | – | – | – | 88.5%#2 |
Maths
| Benchmark | no reasoning | low | xhigh | max | Source | Trend |
|---|---|---|---|---|---|---|
| FrontierMath Tiers 1–3 | – | – | – | 89.1%#6 | Epoch AI Benchmarking Hub | |
| FrontierMath Tier 4 | – | – | – | 82.9%#11 | Epoch AI Benchmarking Hub | |
| OTIS Mock AIME | 68.9%#141 | 95.6%#44 | – | 100.0%#1 | Epoch AI Benchmarking Hub | |
| ProofBench | – | – | – | 83.0%#12 | Vals AI | |
| LiveBench Mathematicsnot in index | – | – | – | 96.2%#10 | LiveBench | |
| Arena Maths | – | – | 1496#22 | – | Arena (LMArena) |
Knowledge
| Benchmark | no reasoning | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|---|
| SimpleQA Verified | – | – | – | – | – | 69.7%#8 | – | Epoch AI Benchmarking Hub | |
| LiveBench 2.0 Data Analysisnot in indexeffort not stated | – | – | – | – | – | – | 79.8%#10 | LiveBench | |
| LiveBench Researchnot in indexeffort not stated | – | – | – | – | – | – | 54.5%#45 | LiveBench | |
| LiveBench 1.0 Data Analysisnot in index | – | – | – | – | – | 79.8%#10 | – | LiveBench | |
| AA-Omniscience | 1.1#125 | 18.9#73 | 19.4#71 | 20.4#68 | 21.0#63 | 22.0#60 | – | Artificial Analysis | |
| MMLU-Pro | – | – | – | – | – | 89.1%#16 | – | Vals AI | |
| LegalBench | – | – | – | – | – | 87.0%#9 | – | Vals AI | |
| CorpFin | – | – | – | – | – | 64.4%#38 | – | Vals AI | |
| TaxEval | – | – | – | – | – | 74.8%#28 | – | Vals AI | |
| PRBench Finance | – | – | – | – | – | 50.5%#10 | – | Scale AI SEAL | |
| PRBench Legal | – | – | – | – | – | 50.5%#9 | – | Scale AI SEAL | |
| BioMysteryBenchnot in index | – | – | – | – | – | 71.1%#11 | – | Vals AI | |
| Excel Modeling Benchmarknot in index | – | – | – | – | – | 72.3%#7 | – | Vals AI | |
| MedCodenot in index | – | – | – | – | – | 44.0%#43 | – | Vals AI | |
| MedScribenot in index | – | – | – | – | – | 85.2%#30 | – | Vals AI | |
| Public Benefits Bench v1.1not in index | – | – | – | – | – | 66.5%#17 | – | Vals AI | |
| DrugDiscoveryBenchnot in index | – | – | – | – | – | 56.5%#4 | – | Scale AI SEAL | |
| EBR-benchnot in index | – | – | – | – | – | 44.8%#8 | – | Epoch AI Benchmarking Hub | |
| GDP.pdfnot in index | – | – | – | – | – | 30.7%#5 | 30.7%#5 | Epoch AI Benchmarking Hub | |
| AA-Omniscience: accuracynot in index | 48.7%#70 | 57.2%#30 | 57.8%#29 | 58.4%#27 | 58.8%#26 | 59.4%#23 | – | Artificial Analysis | |
| AA-Omniscience: non-hallucinationnot in index | 7.2%#488 | 10.6%#407 | 9.2%#433 | 8.8%#446 | 8.1%#468 | 7.8%#475 | – | Artificial Analysis |
Instruction following
| Benchmark | low | medium | high | xhigh | max | Source | Trend |
|---|---|---|---|---|---|---|---|
| LiveBench Languagenot in index | – | – | – | – | 87.7%#8 | LiveBench | |
| LiveBench Instruction Followingnot in index | – | – | – | – | 71.8%#22 | LiveBench | |
| IFBench | 66.5%#94 | 69.6%#73 | 69.2%#74 | 71.0%#62 | 72.7%#46 | Artificial Analysis | |
| Arena Instruction Followingnot in index | – | – | – | 1491#13 | – | Arena (LMArena) |
Human preference
| Benchmark | xhigh | not stated | Source | Trend |
|---|---|---|---|---|
| Arena Text | 1485#21 | – | Arena (LMArena) | |
| EQ-Bench 4effort not stated | – | 1250#9 | EQ-Bench | |
| Arena Creative Writingnot in index | 1470#17 | – | Arena (LMArena) | |
| Arena Multi-turnnot in index | 1490#22 | – | Arena (LMArena) | |
| Arena Longer Queriesnot in index | 1499#19 | – | Arena (LMArena) |
Multimodal
| Benchmark | no reasoning | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|---|
| Arena Vision | – | – | – | – | 1281#35 | – | – | Arena (LMArena) | |
| LiveBench Designnot in indexeffort not stated | – | – | – | – | – | – | 81.6%#13 | LiveBench | |
| MMMU-Pro | 71.9%#134 | 81.0%#42 | 81.4%#39 | 81.8%#37 | 82.7%#31 | 83.4%#26 | – | Artificial Analysis | |
| MMMU-Pro (Vals)not in index | – | – | – | – | – | 88.8%#6 | – | Vals AI | |
| MortgageTaxnot in index | – | – | – | – | – | 67.3%#27 | – | Vals AI | |
| SAGEnot in index | – | – | – | – | – | 52.6%#6 | – | Vals AI | |
| Blueprint-Bench 2not in indexeffort not stated | – | – | – | – | – | – | 33.6%#10 | Epoch AI Benchmarking Hub |
Long context
| Benchmark | no reasoning | low | medium | high | xhigh | max | Source | Trend |
|---|---|---|---|---|---|---|---|---|
| AA-LCR | 62.3%#271 | 78.0%#121 | 80.3%#71 | 81.7%#52 | 82.3%#41 | 84.0%#12 | Artificial Analysis | |
| Arena Documentnot in index | – | – | – | – | 1489#8 | – | Arena (LMArena) | |
| MLCRnot in index | – | 23.3%#33 | 26.1%#25 | 24.4%#31 | 27.8%#20 | 30.0%#16 | Artificial Analysis |
Composite
| Benchmark | no reasoning | low | medium | high | xhigh | max | not stated | Source | Trend |
|---|---|---|---|---|---|---|---|---|---|
| Epoch Capabilities Indexnot in indexeffort not stated | – | – | – | – | – | – | 162.8#11 | Epoch AI Benchmarking Hub | |
| LiveBench 2.0effort not stated | – | – | – | – | – | – | 76.3%#15 | LiveBench | |
| LiveBench 1.0not in index | – | – | – | – | – | 81.0%#11 | – | LiveBench | |
| AA Intelligence Index v4.3.2 | 28.3#136 | 33.5#107 | 39.2#71 | 42.4#52 | 44.0#44 | 47.0#29 | – | Artificial Analysis | |
| Vals RSI Indexnot in index | – | – | – | – | – | 23.9%#12 | – | Vals AI | |
| Vals Science Indexnot in index | – | – | – | – | – | 41.5%#9 | – | Vals AI | |
| Vals Multimodal Indexnot in index | – | – | – | – | – | 72.6%#4 | – | Vals AI |
Safety & honesty
| Benchmark | not stated | Source | Trend |
|---|---|---|---|
| FORTRESSnot in index | 20.1%#40 | Scale AI SEAL |
Where it wins
Benchmarks where this configuration ranks in the top five of every configuration measured.
Where to run it
Every provider serving this model through OpenRouter, with throughput and first-token latency measured on live traffic over the last 30 minutes and each provider’s own price. Purple marks the best in each column.
| Provider | Speed | First token | Input $/M | Output $/M | Context | Quantisation |
|---|---|---|---|---|---|---|
| OpenAI | 103 tok/s | 2.56 s | $8.00 | $40.00 | 1.1M | – |
| Amazon Bedrock | 82 tok/s | 1.95 s | $4.40 | $22.00 | 1.1M | – |
| Azure | 70 tok/s | 3.42 s | $4.00 | $20.00 | 1.1M | – |
| OpenAI | 55 tok/s | 1.11 s | $4.00 | $20.00 | 1.1M | – |
| OpenAI | 47 tok/s | 5.58 s | $2.00 | $10.00 | 1.1M | – |
What a task costs
Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.400 per 1M. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0076 | $0.0065 | 1.2 min |
| Summarize a 30-page report | 12,000 / 600 | $0.060 | $0.028 | 1.3 min |
| Code edit | 6,000 / 1,500 | $0.054 | $0.038 | 1.4 min |
| Agentic coding session | 60,000 / 4,000 | $0.320 | $0.158 | 1.9 min |
| Structured extraction | 2,000 / 200 | $0.012 | $0.0066 | 1.2 min |
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- GPT-5.6 Sol vs MiMo-V2.6-Pro
- GPT-5.6 Sol vs DeepSeek V4.1 Flash 1017
- GPT-5.6 Sol vs Grok 4.7
- GPT-5.6 Sol vs GPT-5.3-Codex
- GPT-5.6 Sol vs GLM 5.3
- GPT-5.6 Sol vs Gemini 3.7 Flash
- GPT-5.6 Sol vs Qwen3.8 Max
- GPT-5.6 Sol vs Claude Opus 4.7
- GPT-5.6 Sol vs Claude Opus 4.8
- GPT-5.6 Sol vs GPT-5.4 Pro
- GPT-5.6 Sol vs Muse Spark 1.2
- GPT-5.6 Sol vs Gemini 3.5 Flash
- GPT-5.6 Sol vs Qwen3.8 2.4T A95B
- GPT-5.6 Sol vs Claude Opus 4.6
- GPT-5.6 Sol vs GLM 5.3 Flash
- GPT-5.6 Sol vs Muse Spark 1.1
- GPT-5.6 Sol vs GLM 5.2
- GPT-5.6 Sol vs Qwen3.6 Max
- GPT-5.6 Sol vs Gemini 3.6 Flash
- GPT-5.6 Sol vs MiniMax M3.1 Flash
- GPT-5.6 Sol vs Muse Spark Open
- GPT-5.6 Sol vs Claude Haiku 5.5
- GPT-5.6 Sol vs DeepSeek V4 Pro
- GPT-5.6 Sol vs GPT-5.2
- GPT-5.6 Sol vs Gemini 3.1 Pro
- GPT-5.6 Sol vs Qwen3.7
- GPT-5.6 Sol vs Gemini 3 Pro
- GPT-5.6 Sol vs Step 5 Preview
- GPT-5.6 Sol vs Claude Sonnet 5
- GPT-5.6 Sol vs Qwen3.8-Flash-Next
- GPT-5.6 Sol vs GPT-6 Luna
- GPT-5.6 Sol vs Claude Opus 4.5
- GPT-5.6 Sol vs GPT-5.6 Luna
- GPT-5.6 Sol vs GPT-5 Pro
- GPT-5.6 Sol vs MiMo-V2.6-Flash
- GPT-5.6 Sol vs DeepSeek V4 Pro 0424
- GPT-5.6 Sol vs o3
- GPT-5.6 Sol vs DeepSeek V4 Flash
See also
Questions people ask
- What are GPT-5.6 Sol's benchmark scores?
- As of 24 Oct 2026, GPT-5.6 Sol (max effort) scores 68.0 ±3.7 on the BenchLeader Index, top 25, strongest in composite (82) and weakest in knowledge (65). That rests on 30 independent benchmark results, and every score on this page links to its publisher.
- How does GPT-5.6 Sol rank?
- GPT-5.6 Sol (max effort) is #16 of 785 ranked configurations on 24 Oct 2026 (top 25). 68 other configurations score within its margin, so the exact position matters less than the band. The leader is Claude Opus 5.5 (max effort) at 72.6.
- How much does GPT-5.6 Sol cost per 1M tokens?
- As of 24 Oct 2026, GPT-5.6 Sol costs $4.00 per 1M input tokens and $20.00 per 1M output tokens, $8.00 blended (three input tokens per output token).
- Is GPT-5.6 Sol better than Muse Wonder?
- As of 24 Oct 2026, GPT-5.6 Sol (max) and Muse Wonder (max) are neck and neck on quality (68.0 vs 67.5, inside the ±5.7 margin of error) and cost about the same, so speed decides it: Muse Wonder (max) streams 1.7× faster. The head-to-head page has the benchmark-by-benchmark detail.
- When was GPT-5.6 Sol released?
- OpenAI released GPT-5.6 Sol on 9 Jul 2026. BenchLeader has results for it at 7 reasoning-effort settings.
Data as of 24 Oct 2026. Compare these configurations.
Cite as: BenchLeader, “GPT-5.6 Sol: benchmarks, pricing, speed and rank”, data as of 24 Oct 2026, https://www.benchleader.com/models/gpt-5-6-sol.