GPT-5.6 Sol vs Qwen3.6 Max
Full profiles: GPT-5.6 Sol (OpenAI) and Qwen3.6 Max (Alibaba): every benchmark, price and rank.
Updated · Data from 10 sources
As of 27 Oct 2026, GPT-5.6 Sol (max) leads on quality (67.8 vs 62.2 on the BenchLeader Index), but Qwen3.6 Max (max) costs 2.7× less, so it is the better buy unless you need the extra quality. Pick GPT-5.6 Sol for reasoning (72 vs 58); pick Qwen3.6 Max for agents & tools (72 vs 67).
GPT-5.6 Sol benchmarks 
Qwen3.6 Max benchmarks Which to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | GPT-5.6 Sol | 66 vs 57 category score; SWE-bench (Vals) 96.2% vs 72.8% | High |
| Agents & tool use | Qwen3.6 Max | 72 vs 67 category score; Terminal-Bench Hard 43.9% vs 65.9% | Medium |
| Maths | GPT-5.6 Sol | 71 vs 65 category score; OTIS Mock AIME 100.0% vs 91.1% | Medium |
| Reasoning | GPT-5.6 Sol | 72 vs 58 category score; GPQA Diamond 93.5% vs 87.4% | High |
| Knowledge | GPT-5.6 Sol | 65 vs 62 category score; SimpleQA Verified 69.7% vs 52.0% | Medium |
| Long documents | GPT-5.6 Sol | 67 vs 65 category score; AA-LCR 84.0% vs 80.7% | Medium |
| Following instructions | Qwen3.6 Max | 75 vs 71 category score; IFBench 76.6% vs 72.7% | Medium |
| Chat quality (human preference) | – | Only Qwen3.6 Max has an Arena rating (65 category score) | Not comparable |
| Lowest cost | Qwen3.6 Max | $2.92 vs $8.00 per 1M blended; agentic coding session $0.109 vs $0.320 | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GPT-5.6 Sol (max) leads on quality: 67.8 vs 62.2.
- GPT-5.6 Sol (max) is stronger in coding, composite, knowledge, long context, maths, multimodal, reasoning.
- Qwen3.6 Max (max) is stronger in agents & tools, instruction following, human preference.
- Qwen3.6 Max (max) is 2.7× cheaper ($2.92 vs $8.00 per 1M blended).
At a glance
| Spec | GPT-5.6 Sol | Qwen3.6 Max |
|---|---|---|
| Developer | OpenAI | Alibaba |
| Released | 9 Jul 2026 | 20 Apr 2026 |
| Context window (tokens) | 1,050,000 | 262,144 |
| Compared at | GPT-5.6 Sol (max) | Qwen3.6 Max (max) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $4.00 / $20.00 / $0.400 | $1.30 / $7.80 / $0.130 |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | GPT-5.6 Sol (max) | Qwen3.6 Max (max) | Leader |
|---|---|---|---|
| Reasoning | 72.2 | 58.1 | GPT-5.6 Sol |
| Coding | 65.9 | 56.6 | GPT-5.6 Sol |
| Agents & tools | 66.5 | 72.1 | Qwen3.6 Max |
| Maths | 71.0 | 64.9 | GPT-5.6 Sol |
| Knowledge | 65.2 | 62.1 | GPT-5.6 Sol |
| Instruction following | 71.1 | 74.6 | Qwen3.6 Max |
| Human preference | – | 64.8 | not comparable |
| Multimodal | 66.2 | – | not comparable |
| Long context | 67.0 | 65.2 | GPT-5.6 Sol |
| Composite | 81.5 | 60.9 | GPT-5.6 Sol |
Where sources disagree
Across the 17 benchmarks both have, GPT-5.6 Sol leads 13, Qwen3.6 Max leads 4. Every overall index that rates both puts GPT-5.6 Sol ahead.
| Overall index | GPT-5.6 Sol (max) | Qwen3.6 Max (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 67.8 | 62.2 | GPT-5.6 Sol |
| AA Intelligence Index v4.3.2 | 47.0 | 28.4 | GPT-5.6 Sol |
| Arena Text | 1485† | 1461 | GPT-5.6 Sol |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | GPT-5.6 Sol (max) | Qwen3.6 Max (max) |
|---|---|---|
| Blended price per 1M tokens | $8.00 | $2.92 |
| Input / output per 1M | $4.00 / $20.00 | $1.30 / $7.80 |
| Cached input per 1M | $0.400 | $0.130 |
| Price per task: chat reply | $0.0076 | $0.0029 |
| Price per task: summarize a 30-page report | $0.060 | $0.020 |
| Price per task: code edit | $0.054 | $0.019 |
| Price per task: agentic coding session | $0.320 | $0.109 |
| Price per task: structured extraction | $0.012 | $0.0042 |
| Cost to run a full benchmark suite | $1.99 | – |
| Output speed | 81 tok/s | – |
| Time to first answer | 107.7 s | – |
| Time to a complete answer | 113.9 s | – |
Each model is compared at its best-ranked reasoning-effort setting. GPT-5.6 Sol (max) scores 67.8 and takes 108 s to its first answer token; GPT-5.6 Sol (xhigh) scores 66.5 in 56 s, GPT-5.6 Sol (high) scores 66.1 in 10 s. Qwen3.6 Max (max) scores 62.2. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
133 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | GPT-5.6 Sol (max) | Qwen3.6 Max (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 67.8 | 62.2 |
| Agents & tools score | BenchLeader | 66.5 | 72.1 |
| Coding score | BenchLeader | 65.9 | 56.6 |
| Composite score | BenchLeader | 81.5 | 60.9 |
| Instruction following score | BenchLeader | 71.1 | 74.6 |
| Knowledge score | BenchLeader | 65.2 | 62.1 |
| Long context score | BenchLeader | 67.0 | 65.2 |
| Maths score | BenchLeader | 71.0 | 64.9 |
| Multimodal score | BenchLeader | 66.2 | – |
| Reasoning score | BenchLeader | 72.2 | 58.1 |
| Human preference score | BenchLeader | – | 64.8 |
| Blended price $/M | BenchLeader | $8.00 | $2.92 |
| Output speed | BenchLeader | 81 tok/s | – |
| Time to first answer | BenchLeader | 107.7 s | – |
| Context window | BenchLeader | 1,050,000 tokens | 262,144 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 93.5% | 87.4% |
| SimpleBench | SimpleBench | 64.8%† | 63.0% |
| Arena Hard Prompts | Arena (LMArena) | 1512† | 1483 |
| LiveBench 1.0 Reasoning | LiveBench | 91.7% | – |
| GPQA Diamond (AA) | Artificial Analysis | 94.1% | 88.8% |
| Humanity's Last Exam (AA) | Artificial Analysis | 49.5% | 30.8% |
| GPQA Diamond (Vals) | Vals AI | 95.2% | – |
| EnigmaEval | Scale AI SEAL | 37.1%† | – |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 67.0%† | – |
| ARC-AGI-1 | ARC Prize | 96.5% | – |
| ARC-AGI-2 | ARC Prize | 92.5% | – |
| ARC-AGI-3 | ARC Prize | 7.8% | – |
| CritPt | Artificial Analysis | 32.3% | 3.7% |
| MysteryMechanism | Vals AI | 33.3% | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 59.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 58.0% | 19.0%† |
| LMCA | Epoch AI Benchmarking Hub | 58.4% | 42.5% |
| DTBench | Epoch AI Benchmarking Hub | 95.5% | 87.2% |
| ForecastBench | ForecastBench | 65.5% | – |
| BTF-3 | Epoch AI Benchmarking Hub | 13.7% | – |
| Coding | |||
| SWE-bench Verified (Epoch) | Epoch AI Benchmarking Hub | – | 76.7% |
| SciCode | SciCode | 57.1% | – |
| WeirdML | WeirdML | 87.0% | – |
| FrontierCode | Cognition | 47.5%† | – |
| GSO-Bench | GSO-Bench | 76.5%† | – |
Show all 133 benchmarks
| Metric | Publisher | GPT-5.6 Sol (max) | Qwen3.6 Max (max) |
|---|---|---|---|
| Coding | |||
| Arena Coding | Arena (LMArena) | 1534† | 1512 |
| Arena WebDev | Arena (LMArena) | 1615† | 1482 |
| LiveBench 1.0 Coding | LiveBench | 83.9% | – |
| LiveCodeBench | Vals AI | 82.6% | – |
| IOI | Vals AI | 91.2% | – |
| SWE-bench (Vals) | Vals AI | 96.2% | 72.8% |
| Code Migration | Vals AI | 52.9% | – |
| ProgramBench | Vals AI | 1.5% | – |
| Vibe Code Bench 1-100 | Vals AI | 20.0% | – |
| Vibe Code Bench v1.1 | Vals AI | 80.5% | – |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 46.0%† | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 45.9%† | – |
| MirrorCode | Epoch AI Benchmarking Hub | 20.0%† | – |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 93.1%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 72.7% | – |
| CursorBench | Cursor | 41.7% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2176.9 | – |
| FrontierSWE | Epoch AI Benchmarking Hub | 32.2% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 39.9% | – |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 88.0% | – |
| Startrise Frontend | Startrise | 66.2%† | – |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 37.3% | – |
| OSWorld-Verified 2.0 | OSWorld | 27.3% | – |
| Arena Agent | Arena (LMArena) | 6.1† | – |
| LiveBench Agentic Coding | LiveBench | 56.2% | – |
| Terminal-Bench Hard | Artificial Analysis | 65.9% | 43.9% |
| τ²-Bench Telecom (AA) | Artificial Analysis | 85.1% | 95.9% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 85.8% | – |
| HiL-Bench | Scale AI SEAL | 32.3%† | – |
| τ³-bench Banking | τ²-bench | 46.9%† | – |
| τ³-Banking (AA) | Artificial Analysis | 44.3% | – |
| ITBench SRE (AA) | Artificial Analysis | 56.2% | – |
| Analyst Agent (AA) | Artificial Analysis | 47.5% | – |
| CUA-bench | Vals AI | 8.3% | – |
| CyberBench | Vals AI | 76.3% | – |
| Finance Agent v2 | Vals AI | 53.8% | – |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 2.5% | – |
| Legal Research Bench | Vals AI | 48.1% | – |
| SkillsBench | Vals AI | 54.1% | – |
| SREBench | Vals AI | 30.5% | – |
| Tax Agent Bench | Vals AI | 31.1% | – |
| Terminal-Bench 2.0 (Vals) | Vals AI | – | 51.7% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 37.9% | – |
| Terminal-Bench Science | Vals AI | 20.0% | – |
| Time Horizon Index: KSP | Vals AI | 23.8% | – |
| Web Search Index | Vals AI | 43.6% | – |
| Arena Search | Arena (LMArena) | 1258† | – |
| BALROG | BALROG | 60.0% | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 36.2% | – |
| GBAEval | Epoch AI Benchmarking Hub | 52.6%† | – |
| Vending-Bench 2 | Andon Labs | 9619.4† | 4254.2 |
| AutomationBench | Artificial Analysis | 60.1% | – |
| GDP.pdf (AA) | Artificial Analysis | 27.2% | – |
| EnterpriseOps-Gym | Artificial Analysis | 42.9% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1479 | – |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 22.4% | – |
| FACTS Search | 88.5%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 89.1% | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 82.9% | – |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | 91.1% |
| ProofBench | Vals AI | 83.0% | – |
| LiveBench Mathematics | LiveBench | 96.2% | – |
| Arena Maths | Arena (LMArena) | 1496† | 1476 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 69.7% | 52.0% |
| LiveBench 1.0 Data Analysis | LiveBench | 79.8% | – |
| AA-Omniscience | Artificial Analysis | 22.0 | 9.2 |
| MMLU-Pro | Vals AI | 89.1% | – |
| LegalBench | Vals AI | 87.0% | – |
| CorpFin | Vals AI | 64.4% | 66.5% |
| TaxEval | Vals AI | 74.8% | – |
| PRBench Finance | Scale AI SEAL | 50.5% | – |
| PRBench Legal | Scale AI SEAL | 50.5% | – |
| BioMysteryBench | Vals AI | 71.1% | – |
| CaseLaw v2 | Vals AI | – | 47.9% |
| Excel Modeling Benchmark | Vals AI | 72.3% | – |
| MedCode | Vals AI | 44.0% | – |
| MedScribe | Vals AI | 85.2% | – |
| Public Benefits Bench v1.1 | Vals AI | 66.5% | – |
| DrugDiscoveryBench | Scale AI SEAL | 56.5% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 44.8% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 30.7% | – |
| AA-Omniscience: accuracy | Artificial Analysis | 59.4% | 37.9% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 7.8% | 53.8% |
| Instruction following | |||
| LiveBench Language | LiveBench | 87.7% | – |
| LiveBench Instruction Following | LiveBench | 71.8% | – |
| IFBench | Artificial Analysis | 72.7% | 76.6% |
| Arena Instruction Following | Arena (LMArena) | 1491† | 1452 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1485† | 1461 |
| EQ-Bench 4 | EQ-Bench | 1240† | – |
| Arena Creative Writing | Arena (LMArena) | 1470† | 1438 |
| Arena Multi-turn | Arena (LMArena) | 1490† | 1468 |
| Arena Longer Queries | Arena (LMArena) | 1499† | 1474 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1281† | – |
| MMMU-Pro | Artificial Analysis | 83.4% | – |
| MMMU-Pro (Vals) | Vals AI | 88.8% | – |
| MortgageTax | Vals AI | 67.3% | – |
| SAGE | Vals AI | 52.6% | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 33.6%† | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 84.0% | 80.7% |
| Arena Document | Arena (LMArena) | 1489† | – |
| MLCR | Artificial Analysis | 30.0% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 162.8† | 149.4 |
| LiveBench 1.0 | LiveBench | 81.0% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 47.0 | 28.4 |
| Vals RSI Index | Vals AI | 23.9% | – |
| Vals Science Index | Vals AI | 41.5% | – |
| Vals Multimodal Index | Vals AI | 72.6% | – |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 20.1%† | – |
Data as of 2026-10-27. Best configuration of each model; every score links to its source on the model pages.
What changed
- GPT-5.6 Sol (max): 1 new result (AA-Briefcase v1.1).
- GPT-5.6 Sol (max): 3 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index, Vals Science Index).
- GPT-5.6 Sol (max): 1 score revision.
- GPT-5.6 Sol (max): 1 new result (ForecastBench).
- GPT-5.6 Sol (max): 5 new results (AutomationBench, GDP.pdf (AA), MLCR…).
- Qwen3.6 Max (max): BenchLeader Index 62.8 → 62.3.
- GPT-5.6 Sol (max): 1 score revision.
- GPT-5.6 Sol (max): 1 score revision.
- GPT-5.6 Sol (max): 1 new result (PRBench Legal).
- GPT-5.6 Sol (max): 1 new result (DrugDiscoveryBench).
Related comparisons
- GPT-5.6 Sol vs Claude Opus 5.5
- GPT-5.6 Sol vs Claude Fable 5.1
- GPT-5.6 Sol vs GPT-6 Astra
- Qwen3.6 Max vs Claude Opus 5.5
- Qwen3.6 Max vs Claude Fable 5.1
- Qwen3.6 Max vs GPT-6 Astra
- Qwen3.6 Max vs Muse Wonder Full
- GPT-5.5 vs Qwen3.6 Max
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GPT-5.6 Sol vs Qwen3.6 Max: questions
- Is GPT-5.6 Sol better than Qwen3.6 Max?
- GPT-5.6 Sol (max) leads on quality: 67.8 vs 62.2. The BenchLeader Index combines every independent quality benchmark; GPT-5.6 Sol (max) is ahead overall as of 2026-10-27, but check the category scores for your use.
- Which is cheaper, GPT-5.6 Sol or Qwen3.6 Max, and will that change?
- Qwen3.6 Max is cheaper today: $2.92 against $8.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GPT-5.6 Sol better than Qwen3.6 Max for coding?
- GPT-5.6 Sol scores higher in coding (66 vs 57 on the category index, where 50 is average).
- Is GPT-5.6 Sol better than Qwen3.6 Max for agents and tool use?
- Qwen3.6 Max scores higher in agentic tasks (72 vs 67 on the category index, where 50 is average). On Terminal-Bench Hard, the top shared agents & tools benchmark, it is 65.9% for GPT-5.6 Sol against 43.9% for Qwen3.6 Max.
- Which is better for long documents?
- GPT-5.6 Sol scores higher on long-context benchmarks (67 vs 65). GPT-5.6 Sol accepts more context: 1,050,000 against 262,144 tokens for Qwen3.6 Max.
- Do independent benchmarks agree on GPT-5.6 Sol vs Qwen3.6 Max?
- Across the 17 benchmarks both have, GPT-5.6 Sol leads 13, Qwen3.6 Max leads 4. Every overall index that rates both puts GPT-5.6 Sol ahead.
- When was GPT-5.6 Sol released?
- GPT-5.6 Sol was released on 9 Jul 2026.