AlibabaQwen3.6 Max
Qwen3.6 Max is an Alibaba proprietary reasoning model, released 20 Apr 2026. Its best configuration (max reasoning effort) ranks #87 of 785 on the BenchLeader Index at 62.3 ±3.0, in the upper half. The ± is the point: 166 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 instruction following (75) and lowest in coding (57). At $2.92 per million tokens blended it is pricier than most ranked models. It has been measured at 2 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 22 Oct 2026.
- Blended price
- $2.92/M
- $1.30 in · $7.80 out
- Output speed
- –
- First answer
- –
- Context
- 262k
- Full answer
- –
- Cost per run
- –
- Released
- 20 Apr 2026
- Overall index62
- Reasoning58
- Coding57
- Agents & tools72
- Maths65
- Knowledge62
- Instruction following75
- Human preference65
- Long context65
- Composite61
Versions
Alibaba 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 |
|---|---|---|---|
| Qwen3.8 Maxmax | 3 Aug 2026 | 63.3 | #65 |
| Qwen3.6 Maxmaxthis page | 20 Apr 2026 | 62.3 | #87 |
| Qwen3.5 Maxmax | – | – | – |
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 | – | – | – | – | – | |
| maxbest | 62.3 | #87 | – | – | $0.0029 | Agents & tools 72 · Coding 57 · Composite 61 · Human preference 65 · Instruction following 75 · Knowledge 62 · Long context 65 · Maths 65 · Reasoning 58 |
How its index has moved
9 Sept 2026 to 21 Oct 2026The 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 | max | Source | Trend |
|---|---|---|---|---|
| GPQA Diamond | – | 87.4%#73 | Epoch AI Benchmarking Hub | |
| SimpleBench | – | 63.0%#20 | SimpleBench | |
| Arena Hard Prompts | – | 1483#62 | Arena (LMArena) | |
| GPQA Diamond (AA)not in index | – | 88.8%#86 | Artificial Analysis | |
| Humanity's Last Exam (AA)not in index | – | 30.8%#143 | Artificial Analysis | |
| CritPt | – | 3.7%#171 | Artificial Analysis | |
| Mystery Game Puzzlesnot in index | 19.0%#64 | – | Epoch AI Benchmarking Hub | |
| LMCAnot in index | – | 42.5%#101 | Epoch AI Benchmarking Hub | |
| DTBenchnot in index | – | 87.2%#101 | Epoch AI Benchmarking Hub |
Coding
| Benchmark | max | Source | Trend |
|---|---|---|---|
| SWE-bench Verified (Epoch) | 76.7%#9 | Epoch AI Benchmarking Hub | |
| Arena Coding | 1512#53 | Arena (LMArena) | |
| Arena WebDev | 1482#64 | Arena (LMArena) | |
| SWE-bench (Vals)not in index | 72.8%#52 | Vals AI |
Agents & tools
| Benchmark | max | Source | Trend |
|---|---|---|---|
| Terminal-Bench Hard | 43.9%#37 | Artificial Analysis | |
| τ²-Bench Telecom (AA)not in index | 95.9%#15 | Artificial Analysis | |
| Terminal-Bench 2.0 (Vals)not in index | 51.7%#18 | Vals AI | |
| Vending-Bench 2not in index | 4254.2#40 | Andon Labs |
Maths
| Benchmark | max | Source | Trend |
|---|---|---|---|
| OTIS Mock AIME | 91.1%#70 | Epoch AI Benchmarking Hub | |
| Arena Maths | 1476#45 | Arena (LMArena) |
Knowledge
| Benchmark | max | Source | Trend |
|---|---|---|---|
| SimpleQA Verified | 52.0%#24 | Epoch AI Benchmarking Hub | |
| AA-Omniscience | 9.2#97 | Artificial Analysis | |
| CorpFin | 66.5%#18 | Vals AI | |
| CaseLaw v2not in index | 47.9%#50 | Vals AI | |
| AA-Omniscience: accuracynot in index | 37.9%#138 | Artificial Analysis | |
| AA-Omniscience: non-hallucinationnot in index | 53.8%#103 | Artificial Analysis |
Instruction following
| Benchmark | max | Source | Trend |
|---|---|---|---|
| IFBench | 76.6%#19 | Artificial Analysis | |
| Arena Instruction Followingnot in index | 1452#63 | Arena (LMArena) |
Human preference
| Benchmark | max | Source | Trend |
|---|---|---|---|
| Arena Text | 1461#60 | Arena (LMArena) | |
| Arena Creative Writingnot in index | 1438#60 | Arena (LMArena) | |
| Arena Multi-turnnot in index | 1468#64 | Arena (LMArena) | |
| Arena Longer Queriesnot in index | 1474#57 | Arena (LMArena) |
Long context
| Benchmark | max | Source | Trend |
|---|---|---|---|
| AA-LCR | 80.7%#65 | Artificial Analysis |
Composite
| Benchmark | max | Source | Trend |
|---|---|---|---|
| Epoch Capabilities Indexnot in index | 149.4#63 | Epoch AI Benchmarking Hub | |
| AA Intelligence Index v4.3.2 | 28.4#135 | Artificial Analysis |
Price history
The price above, per 1M tokens, every day it changed.
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 $0.130 per 1M. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0029 | $0.0025 | – |
| Summarize a 30-page report | 12,000 / 600 | $0.020 | $0.0098 | – |
| Code edit | 6,000 / 1,500 | $0.019 | $0.014 | – |
| Agentic coding session | 60,000 / 4,000 | $0.109 | $0.057 | – |
| Structured extraction | 2,000 / 200 | $0.0042 | $0.0024 | – |
Compare Qwen3.6 Max with…
- Qwen3.6 Max vs Claude Opus 5.5
- Qwen3.6 Max vs Gemini 4 Argon
- Qwen3.6 Max vs Muse Wonder Full
- Qwen3.6 Max vs Claude Fable 5.1
- Qwen3.6 Max vs GPT-6 Astra
- Qwen3.6 Max vs GPT-6.1 Sol
- Qwen3.6 Max vs Claude Fable 5
- Qwen3.6 Max vs Claude Sonnet 5.5
- Qwen3.6 Max vs Claude Opus 5
- Qwen3.6 Max vs GPT-5.6 Sol
- Qwen3.6 Max vs Muse Wonder
- Qwen3.6 Max vs Muse Spark 1.3
- Qwen3.6 Max vs Kimi K3.1 Pro
- Qwen3.6 Max vs GPT-6 Sol
- Qwen3.6 Max vs GPT-5.5
- Qwen3.6 Max vs GPT-5.5 Pro
- Qwen3.6 Max vs GPT-5.4
- Qwen3.6 Max vs Kimi K3
- Qwen3.6 Max vs Gemini 3.8 Flash
- Qwen3.6 Max vs GPT-5.6 Terra
- Qwen3.6 Max vs Muse Spark
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- Qwen3.6 Max vs MiMo-V2.6-Pro
- Qwen3.6 Max vs DeepSeek V4.1 Flash 1017
- Qwen3.6 Max vs Grok 4.7
- Qwen3.6 Max vs GPT-5.3-Codex
- Qwen3.6 Max vs GLM 5.3
- Qwen3.6 Max vs Gemini 3.7 Flash
- Qwen3.6 Max vs Qwen3.8 Max
- Qwen3.6 Max vs Claude Opus 4.7
- Qwen3.6 Max vs Claude Opus 4.8
- Qwen3.6 Max vs GPT-5.4 Pro
- Qwen3.6 Max vs Muse Spark 1.2
- Qwen3.6 Max vs Gemini 3.5 Flash
- Qwen3.6 Max vs Qwen3.8 2.4T A95B
- Qwen3.6 Max vs Claude Opus 4.6
- Qwen3.6 Max vs GLM 5.3 Flash
- Qwen3.6 Max vs Muse Spark 1.1
- Qwen3.6 Max vs GLM 5.2
See also
Questions people ask
- What are Qwen3.6 Max's benchmark scores?
- As of 24 Oct 2026, Qwen3.6 Max (max effort) scores 62.3 ±3.0 on the BenchLeader Index, top 100, strongest in instruction following (75) and weakest in coding (57). That rests on 17 independent benchmark results, and every score on this page links to its publisher.
- How does Qwen3.6 Max rank?
- Qwen3.6 Max (max effort) is #87 of 785 ranked configurations on 24 Oct 2026 (top 100). 166 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 Qwen3.6 Max cost per 1M tokens?
- As of 24 Oct 2026, Qwen3.6 Max costs $1.30 per 1M input tokens and $7.80 per 1M output tokens, $2.92 blended (three input tokens per output token). The list price last changed on 24 Oct 2026.
- Is Qwen3.6 Max better than GLM 5.2?
- As of 24 Oct 2026, GLM 5.2 (max) and Qwen3.6 Max (max) are neck and neck on quality (62.3 vs 62.3 on the BenchLeader Index, inside the ±4.7 margin of error), and GLM 5.2 (max) costs 1.4× less, which makes it the better buy for most workloads. The head-to-head page has the benchmark-by-benchmark detail.
- When was Qwen3.6 Max released?
- Alibaba released Qwen3.6 Max on 20 Apr 2026. BenchLeader has results for it at 2 reasoning-effort settings.
Data as of 24 Oct 2026. Compare these configurations.
Cite as: BenchLeader, “Qwen3.6 Max: benchmarks, pricing, speed and rank”, data as of 24 Oct 2026, https://www.benchleader.com/models/qwen3-6-max.