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The LLM benchmark aggregator.

Qwen Max

Alibaba

Strongest in Toxicity avoidance (#66 of 268), weakest in Human preference (#212 of 354). Above par in 5 of 8 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 4.7 and Claude Sonnet 5 and ahead of Kimi K2.5 and IBM Granite 4.0 Micro.

§ 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.

Safety53.2#90/329
Toxicity avoidance56.2#66/268
Jailbreak resistance57.8#70/268
Secure code56.6#99/270
Harm refusal52.8#112/292
Fairness46.2#160/292
Human preference48.8#212/354
Human preference48.8#212/354

§ 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 Qwen Max, left for the other.

Jamba 1.6 Largewon 5 · lost 0
DeepSeek Reasonerwon 5 · lost 0
Qwen1.5 72B Chatwon 5 · lost 0
Command Rwon 5 · lost 0
OLMoE 1B-7B Instructwon 6 · lost 0
SmolLM 1.7B Instructwon 6 · lost 0
H2o Danube3 500M Chatwon 6 · lost 0
Laguna Xs 2.1won 6 · lost 0
RakutenAI 7B Instructwon 6 · lost 0
CodeLlama 7B Instructwon 6 · lost 0
Qwen2.5 0.5B Instructwon 6 · lost 0
Magistral Smallwon 6 · lost 0
Aya 23 8Bwon 6 · lost 0
Laguna S 2.1won 6 · lost 0
H2o Danube3 4B Chatwon 6 · lost 0
Ling 3.0 Flash VLwon 6 · lost 0
Jamba 1.6 Miniwon 6 · lost 0
Ling 3.0 Flashwon 6 · lost 0
Phi-4 Mini Instructwon 6 · lost 0
Qwen2.5 3B Instructwon 6 · lost 0
Jamba Instructwon 6 · lost 0
Qwen2.5 7B Instruct 1Mwon 6 · lost 0
SeaLLMs V3 7B Chatwon 6 · lost 0
Qwen2.5 1.5B Instructwon 6 · lost 0
DeepSeek Chatwon 6 · lost 0
Qwen2.5 32B Instructwon 6 · lost 0
Qwen2.5 14B Instructwon 6 · lost 0
SmolLM2 1.7B Instructwon 8 · lost 0
Zephyr 7B Betawon 8 · lost 0
DeepSeek LLM 67B Chatwon 8 · lost 0
DBRX Instructwon 8 · lost 0
Mixtral 8x7B Instructwon 8 · lost 0
GPT-3.5 Turbowon 8 · lost 0
Command R+won 8 · lost 0
Jamba 1.5 Largewon 8 · lost 0
Gemma 3 4B ITwon 8 · lost 0
Magistral Mediumwon 8 · lost 0
Llama 3.3 70B Instructwon 8 · lost 0
OLMo 7B Instructwon 7 · lost 1
Gemma 2B ITwon 7 · lost 1
Gemma 7B ITwon 7 · lost 1
Llama 3.2 3B Instructwon 7 · lost 1
Qwen1.5 14B Chatwon 7 · lost 1
Llama 3.1 8B Instructwon 7 · lost 1
Mixtral 8x22B Instructwon 7 · lost 1
Jamba 1.5 Miniwon 7 · lost 1
Gemma 2 9B ITwon 7 · lost 1
Amazon Nova Prowon 7 · lost 1
Llama 3.1 70B Instructwon 7 · lost 1
RakutenAI 7B Chatwon 5 · lost 1
PowerMoE 3Bwon 5 · lost 1
Phi 2won 5 · lost 1
PowerLM 3Bwon 5 · lost 1
LFM2 350Mwon 5 · lost 1
GLM-4 9B Chatwon 5 · lost 1
SmolLM2 360M Instructwon 5 · lost 1
Qwen2 7B Instructwon 5 · lost 1
Jamba Mini 1.7won 5 · lost 1
OLMo 2 7B Instructwon 5 · lost 1
Magistral Small 1.2won 5 · lost 1
SEA LION V1 7B ITwon 5 · lost 1
Grok Build 0.1won 5 · lost 1
Command R7Bwon 5 · lost 1
LFM2 700Mwon 5 · lost 1
Jamba Large 1.7won 5 · lost 1
NexusRaven V2 13Bwon 5 · lost 1
SmolLM 360M Instructwon 5 · lost 1
Qwen3 8Bwon 5 · lost 1
Open Codestral Mambawon 5 · lost 1
Aya 23 35Bwon 5 · lost 1
LFM2 1.2Bwon 5 · lost 1
Gemma 4 E2Bwon 5 · lost 1
Yi 1.5 9B Chatwon 5 · lost 1
Sarvam 1won 5 · lost 1
Gemma 4 E4Bwon 5 · lost 1
WizardLM 2.8x22Bwon 5 · lost 1
Kimi K2.7 Codewon 5 · lost 1
Gemma 4 12Bwon 5 · lost 1
Hunyuan A13B Instructwon 5 · lost 1
LongWriter Glm4 9Bwon 5 · lost 1
Qwen2 VL 72Bwon 5 · lost 1
GLM-5 Turbowon 5 · lost 1
Qwen 2.5 Instruct (7B)won 5 · lost 1
Sarvam 30Bwon 5 · lost 1
Kimi K2 Thinkingwon 4 · lost 1
OLMo 2 32B Instructwon 4 · lost 1
Starling LM 7B Betawon 6 · lost 2
Gemma 2 2B ITwon 6 · lost 2
Amazon Nova Microwon 6 · lost 2
Amazon Nova Litewon 6 · lost 2
Gemini 1.5 Flashwon 6 · lost 2
Llama 4 Scout Instructwon 6 · lost 2
QwQ 32Bwon 6 · lost 2
Gemma 3 12B ITwon 6 · lost 2
Command Awon 6 · lost 2
Qwen3 30B A3B Instructwon 6 · lost 2
GLM-4.6won 6 · lost 2
Grok 4.1 Fastwon 6 · lost 2
DeepSeek V4 Flashwon 6 · lost 2
Grok 4.3won 6 · lost 2
MiMo V2.6 Flashwon 6 · lost 2
DeepSeek V4 Prowon 6 · lost 2
Llama 3 8B Instructwon 5 · lost 2
Gemini 3.6 Flashwon 5 · lost 2
Komodo 7B Basewon 4 · lost 2
Fuguwon 4 · lost 2
Apertus 8B Instructwon 4 · lost 2
GPT-5.6 Astrawon 4 · lost 2
GPT OSS Safeguard 20Bwon 4 · lost 2
SeaLLM 7B V2won 4 · lost 2
Granite 4.0 H Microwon 4 · lost 2
Granite 4.0 H Tinywon 4 · lost 2
Phi 3.5 Mini Instructwon 4 · lost 2
K2 Chatwon 4 · lost 2
Krutrim 2 Instructwon 4 · lost 2
EAI SageAlign 8B LoRAwon 4 · lost 2
Llama 3.2 1B Instructwon 5 · lost 3
Phi-3 Mini 4K Instructwon 5 · lost 3
Llama 3.1 Tulu 3 8Bwon 5 · lost 3
Claude 3 Haikuwon 5 · lost 3
Llama 3 70B Instructwon 5 · lost 3
Qwen2.5 72B Instructwon 5 · lost 3
Gemini 2.0 Flash-Litewon 5 · lost 3
Gemini 2.0 Flashwon 5 · lost 3
Gemma 3 27B ITwon 5 · lost 3
DeepSeek V3won 5 · lost 3
GLM-4.5won 5 · lost 3
Grok 3won 5 · lost 3
Grok 4won 5 · lost 3
DeepSeek V3.1won 5 · lost 3
DeepSeek R1won 5 · lost 3
MiniMax M3won 5 · lost 3
Gemma 4 26B A4Bwon 5 · lost 3
Gemini 2.5 Prowon 5 · lost 3
Gemma 4 31Bwon 5 · lost 3
GLM-5.3 Flashwon 5 · lost 3
GLM-5.2won 5 · lost 3
MiMo V2.6 Prowon 5 · lost 3
IBM Granite 4.0 Microwon 3 · lost 2
Kimi K2.5won 4 · lost 3
GPT OSS 20Bwon 3 · lost 3
Apertus 70B Instructwon 3 · lost 3
Phi 3.5 MoE Instructwon 3 · lost 3
Fugu Ultra V2won 3 · lost 3
Llama 2 13B Chatwon 4 · lost 4
Llama 2 70B Chatwon 4 · lost 4
GPT-4won 4 · lost 4
Granite 4.0 H Smallwon 4 · lost 4
GPT-4o miniwon 4 · lost 4
GPT-4.1 nanowon 4 · lost 4
Mercury 2won 4 · lost 4
Gemini 1.5 Prowon 4 · lost 4
Gemini 2.5 Flashwon 4 · lost 4
Mistral Large 4won 4 · lost 4
DeepSeek V3.2won 4 · lost 4
GPT-6 Solwon 4 · lost 4
Kimi K2.6won 4 · lost 4
GLM-5.1won 4 · lost 4
Qwen3.7 Maxwon 4 · lost 4
Gemini 3.5 Flashwon 4 · lost 4
Qwen3.8 Maxwon 4 · lost 4
Gemini 3.8 Flashwon 4 · lost 4
Titan Text Express V1won 2 · lost 3
Grok 3 Miniwon 2 · lost 3
GLM-4.5 Airwon 2 · lost 3
Gemini 3 Prowon 2 · lost 3
Llama 2 7B Chatwon 3 · lost 5
Aya Expanse 8Bwon 3 · lost 5
Qwen2 72B Instructwon 3 · lost 5
Aya Expanse 32Bwon 3 · lost 5
Claude 3 Sonnetwon 3 · lost 5
GPT-4.1 miniwon 3 · lost 5
Qwen3.5 35B A3Bwon 3 · lost 5
Qwen3.5 27Bwon 3 · lost 5
Qwen3.5 122B A10Bwon 3 · lost 5
Kimi K2won 3 · lost 5
GPT-6 Lunawon 3 · lost 5
Qwen3.5 397B A17Bwon 3 · lost 5
MiMo V2.5 Prowon 3 · lost 5
GPT-5.6 Solwon 3 · lost 5
Llama 3.2 Vision (11B)won 2 · lost 4
Llama 3 8B Instruct RRwon 2 · lost 4
Nova Premierwon 2 · lost 4
Sarvam 105Bwon 2 · lost 4
Llama 3.2 Vision (90B)won 2 · lost 4
Claude Sonnet 4.6won 2 · lost 4
Claude Opus 4.6won 2 · lost 4
GPT-5.4won 2 · lost 5
Phi 4won 2 · lost 6
Gemma 2 27B ITwon 2 · lost 6
GPT OSS 120Bwon 2 · lost 6
GPT-4.1won 2 · lost 6
GPT-5.6 Lunawon 2 · lost 6
GPT-5.1won 2 · lost 6
Grok 4.6won 2 · lost 6
Grok 4.5won 2 · lost 6
GPT-5.6 Terrawon 2 · lost 6
GPT-5.5won 2 · lost 6
Claude Opus 5won 2 · lost 6
Gemini 2.5 Flash-Litewon 1 · lost 4
Internlm2 Chat 20Bwon 1 · lost 5
Cogito 671B V2 P1won 1 · lost 5
Claude 3.5 Haikuwon 1 · lost 7
O1 Miniwon 1 · lost 7
GPT-5 nanowon 1 · lost 7
O3 Miniwon 1 · lost 7
Claude 3.5 Sonnetwon 1 · lost 7
Claude 3.7 Sonnetwon 1 · lost 7
GPT-5 miniwon 1 · lost 7
O4 Miniwon 1 · lost 7
O1won 1 · lost 7
Claude Haiku 4.5won 1 · lost 7
Claude Opus 4won 1 · lost 7
O3won 1 · lost 7
GPT-5won 1 · lost 7
GPT-5.2won 1 · lost 7
Inklingwon 1 · lost 7
Hy3won 1 · lost 7
Claude Sonnet 4.5won 1 · lost 7
Claude Opus 4.8won 1 · lost 7
Muse Spark 1.1won 1 · lost 7
Claude Opus 5.5won 1 · lost 7
Meta SecAlign 8Bwon 0 · lost 5
GPT-4.5won 0 · lost 5
Apriel 1.5 15B Thinkerwon 0 · lost 6
Claude 3 Opuswon 0 · lost 8
GPT-4 Turbowon 0 · lost 8
GPT-4owon 0 · lost 8
MiniMax M2won 0 · lost 8
Claude Sonnet 4won 0 · lost 8
MiniMax M2.7won 0 · lost 8
Grok 4.7won 0 · lost 8
Claude Sonnet 5won 0 · lost 8
Claude Opus 4.7won 0 · lost 8

§ 3 · Sources

Where the numbers come from

2 publications, 7 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1318
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 6.3%Enkrypt · Harmful content risk 32.8%Enkrypt · CBRN risk 7.7%Enkrypt · Toxicity risk 1.9%Enkrypt · Bias risk 83.7%Enkrypt · Insecure code risk 19.6%

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