The LLM benchmark aggregator.

Qwen3.6 Plus

Alibaba

Strongest in Academic knowledge (#24 of 123), weakest in Core abilities (#172 of 199). Above par in 10 of 18 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5 and Claude Fable 5.1 and ahead of MiMo V2.5 Pro and GLM-4.7.

§ 1 · Profile

What it is good at

Bars run from 50 — the average of the models each source lists — so right of the line is above par. The middle column is the gap to whoever leads that scope.

Knowledge53.4−9.1#54/1971/3

Academic knowledge58.1−5.8#24/1231/1

Human preference60.8−8#76/3541/1

Reasoning52.2−13.2#78/1952/5

Science57.9−5.6#38/1221/1

Mathematics50.2−13.6#85/1522/2

Agents51.4−15#111/2981/6

Knowledge work52.7−18#82/2081/2

Professional48.5−13.9#117/1941/2

Finance53−9.4#73/1621/1

Medical45.9−20.6#114/1491/1

Legal44.1−21.8#126/1731/1

Coding42.5−23.7#149/1792/6

Agentic coding42.2−24.7#142/1732/5

Core abilities42.3−23#172/1991/4

Language45.9−20.7#43/621/1

Instruction following32.8−41#56/621/1

§ 2 · Head to head

What it beats, and what beats it

The same models turn up scope after scope. Counted once: where both were placed, who finished higher. Bars run right for Qwen3.6 Plus, left for the other.

Mistral Small 3.1 24B Instructwon 13 · lost 0

GPT-4o miniwon 15 · lost 0

NVIDIA Nemotron 3.5 Lightning 30B A3Bwon 15 · lost 0

Mistral Medium 3.5won 16 · lost 0

GPT-4.1 nanowon 15 · lost 1

Llama 3.3 70B Instructwon 11 · lost 1

Mistral Medium 3.1won 11 · lost 1

Mistral Large 2.1won 10 · lost 1

Gemini 1.5 Prowon 10 · lost 1

MiMo V2.5won 13 · lost 2

Llama 4 Scout Instructwon 12 · lost 2

Claude 3.5 Haikuwon 12 · lost 2

Gemini 2.5 Flash-Litewon 11 · lost 2

Ling 3.0 Flashwon 10 · lost 2

Qwen3.6 27Bwon 10 · lost 2

Magistral Small 1.2won 9 · lost 2

Magistral Medium 1.2won 9 · lost 2

GPT OSS 120Bwon 13 · lost 3

Command Awon 12 · lost 3

GPT OSS 20Bwon 11 · lost 3

GPT-5 nanowon 10 · lost 3

Gemma 4 31Bwon 9 · lost 3

Llama 4 Maverick Instructwon 12 · lost 4

Mistral Large 3won 12 · lost 4

Gemini 3.1 Flash-Litewon 12 · lost 4

Claude Haiku 4.5won 11 · lost 4

MiniMax M2.7won 11 · lost 4

GPT-5.4 nanowon 13 · lost 5

NVIDIA Nemotron 3 Ultra 550B A55Bwon 13 · lost 5

Grok 4.3won 13 · lost 5

GPT-5.4 miniwon 12 · lost 5

GPT-4owon 10 · lost 5

O3 Miniwon 10 · lost 5

DeepSeek R1won 10 · lost 5

Gemini 2.0 Flashwon 9 · lost 5

Inklingwon 10 · lost 6

GPT-4.1 miniwon 10 · lost 6

GPT-5 miniwon 10 · lost 6

DeepSeek V3won 10 · lost 6

Claude Sonnet 4won 10 · lost 6

MiniMax M2.1won 8 · lost 5

Claude 3.5 Sonnetwon 7 · lost 5

GLM-4.5won 7 · lost 5

Claude 3.7 Sonnetwon 8 · lost 6

Grok 4 Fastwon 8 · lost 6

Qwen3 Maxwon 8 · lost 6

Claude Opus 4won 8 · lost 6

Grok 4.1 Fastwon 8 · lost 6

Grok 4.20won 8 · lost 6

DeepSeek V3.2won 9 · lost 7

GLM-4.6won 9 · lost 7

GPT-6 Lunawon 9 · lost 7

Gemini 2.5 Flashwon 8 · lost 7

Kimi K2won 8 · lost 7

GLM-4.7won 8 · lost 7

MiMo V2.5 Prowon 8 · lost 7

MiniMax M2.5won 7 · lost 7

Grok 3won 7 · lost 7

Qwen3.8 27Bwon 9 · lost 9

GPT-4.1won 7 · lost 8

Qwen3 235B A22B Instructwon 7 · lost 8

Qwen3.5 Flashwon 6 · lost 7

O1won 6 · lost 7

DeepSeek V4won 5 · lost 6

Gemini 3.5 Flash-Litewon 8 · lost 10

Inkling Smallwon 7 · lost 9

GPT-5won 7 · lost 9

Kimi K2.5won 7 · lost 9

Grok 3 Miniwon 6 · lost 8

Kimi K2 Thinkingwon 5 · lost 7

O4 Miniwon 6 · lost 9

Mistral Large 4won 6 · lost 9

O3won 6 · lost 9

MiniMax M3won 7 · lost 11

Gemini 2.5 Prowon 6 · lost 10

GLM-5won 5 · lost 9

Step 5won 4 · lost 8

Grok 4won 5 · lost 10

Grok 4.7won 5 · lost 10

GPT-5.1won 5 · lost 10

DeepSeek V4 Flashwon 6 · lost 12

Claude Sonnet 4.5won 5 · lost 11

Kimi K2.6won 5 · lost 13

GLM-5.3 Flashwon 5 · lost 13

GLM-5.1won 4 · lost 11

Muse Sparkwon 4 · lost 11

Claude Haiku 5.5won 4 · lost 12

GPT-5.2won 4 · lost 13

GPT-5.6 Lunawon 4 · lost 14

GLM-5.2won 4 · lost 14

Claude Opus 4.1won 2 · lost 9

Claude Opus 4.5won 3 · lost 14

Claude Sonnet 4.6won 3 · lost 15

GLM-5.3won 3 · lost 15

Claude Sonnet 5won 2 · lost 15

DeepSeek V4 Prowon 2 · lost 16

GPT-5.4won 2 · lost 16

Gemini 3.5 Flashwon 2 · lost 16

Gemini 3.1 Prowon 2 · lost 16

Muse Spark 1.1won 2 · lost 16

Gemini 3.8 Flashwon 2 · lost 16

MiMo V2.6 Flashwon 1 · lost 12

MiMo V2.6 Prowon 1 · lost 12

GPT-6 Solwon 1 · lost 15

GPT-6.1 Solwon 1 · lost 15

Claude Opus 4.6won 1 · lost 15

Muse Spark 1.2won 1 · lost 16

Grok 4.5won 1 · lost 17

GPT-5.6 Terrawon 1 · lost 17

Qwen3.7 Maxwon 1 · lost 17

Gemini 3.6 Flashwon 1 · lost 17

Muse Wonder Fullwon 0 · lost 11

Kimi K3.1 Prowon 0 · lost 11

Gemini 3 Flashwon 0 · lost 13

Gemini 4 Argonwon 0 · lost 13

Muse Spark 1.3won 0 · lost 14

Muse Wonderwon 0 · lost 14

Gemini 3 Prowon 0 · lost 15

Claude Sonnet 5.5won 0 · lost 16

GPT-6 Astrawon 0 · lost 16

DeepSeek V4.1 Flashwon 0 · lost 16

Claude Opus 5.5won 0 · lost 16

Grok 4.6won 0 · lost 18

GPT-5.5won 0 · lost 18

Claude Opus 4.8won 0 · lost 18

Qwen3.8 Maxwon 0 · lost 18

GPT-5.6 Solwon 0 · lost 18

Kimi K3won 0 · lost 18

Gemini 3.7 Flashwon 0 · lost 18

Claude Opus 5won 0 · lost 18

Claude Opus 4.7won 0 · lost 18

Claude Fable 5.1won 0 · lost 18

Claude Fable 5won 0 · lost 18

§ 3 · Sources

Where the numbers come from

4 publications, 25 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10

LMArena Text 1443

GDPval-AA ↗1 measureread 2026-11-10

GDPval-AA 997

LiveBench 1.0 ↗8 measuresread 2026-11-10

LiveBench 1.0 68.9LiveBench 1.0 · Reasoning 75.8LiveBench 1.0 · Coding 78.2LiveBench 1.0 · Agentic Coding 41.4LiveBench 1.0 · Mathematics 83.7LiveBench 1.0 · Data Analysis 69.9LiveBench 1.0 · Language 75LiveBench 1.0 · Instruction Following 58.3

Vals.ai ↗15 measuresread 2026-11-10

Vals · Legal Research Bench 14.9%Vals · CaseLaw 51.45%Vals · LegalBench 84.23%Vals · Finance Agent 40.85%Vals · CorpFin 61.93%Vals · TaxEval 74.73%Vals · MortgageTax 67.97%Vals · MedCode 36.89%Vals · MedScribe 76.96%Vals · SWE-bench Verified 73.4% (Mini-SWE-agent)Vals · Vibe Code Bench 25.57% (OpenHands)Vals · Code Migration 11.1%Vals · GPQA Diamond 87.37%Vals · MMLU Pro 87.67%Vals · AIME 94.58%

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