The LLM benchmark aggregator.

Qwen3.5 27B

Alibaba · 28B · open weights

Strongest in Secure code (#27 of 268), weakest in Jailbreak resistance (#180 of 266). Above par in 7 of 9 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5.5 and GPT-5.2 and ahead of GPT-5.6 Sol and DeepSeek V4 Pro.

§ 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.

Safety53.4−8#88/3272/3

Secure code63.1−3.1#27/2681/1

Fairness61.1−8.9#35/2901/2

Factual grounding44.5−26.2#80/1041/1

Harm refusal51.4−10.1#130/2901/2

Toxicity avoidance53.7−5.3#132/2661/1

Jailbreak resistance48.6−16.4#180/2661/1

Human preference57.5−11.3#126/3541/1

§ 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 Qwen3.5 27B, left for the other.

OLMoE 1B-7B Instructwon 6 · lost 0

Mistral Instruct v0.1 (7B)won 6 · lost 0

SmolLM 1.7B Instructwon 6 · lost 0

RakutenAI 7B Chatwon 6 · lost 0

PowerMoE 3Bwon 6 · lost 0

Phi 2won 6 · lost 0

PowerLM 3Bwon 6 · lost 0

RakutenAI 7B Instructwon 6 · lost 0

Falcon Mamba 7B Instructwon 6 · lost 0

GLM-4 9B Chatwon 6 · lost 0

SmolLM2 360M Instructwon 6 · lost 0

CodeLlama 7B Instructwon 6 · lost 0

Qwen2.5 0.5B Instructwon 6 · lost 0

Qwen2 7B Instructwon 6 · lost 0

Magistral Smallwon 6 · lost 0

Falcon H1 0.5B Instructwon 6 · lost 0

Grok Build 0.1won 6 · lost 0

LFM2 700Mwon 6 · lost 0

Mimo V2.6 Pro Ultraspeedwon 6 · lost 0

Qwen2.5 3B Instructwon 6 · lost 0

Qwen2.5 7B Instruct 1Mwon 6 · lost 0

GPT-5.6 Astrawon 6 · lost 0

Jamba Mini 1.7won 7 · lost 0

OLMo 7B Instructwon 8 · lost 0

SmolLM2 1.7B Instructwon 8 · lost 0

Zephyr 7B Betawon 8 · lost 0

Gemma 7B ITwon 8 · lost 0

DeepSeek LLM 67B Chatwon 8 · lost 0

Qwen1.5 14B Chatwon 8 · lost 0

Magistral Mediumwon 8 · lost 0

DeepSeek V3won 8 · lost 1

Nous Hermes 2 Mixtral 8x7B DPOwon 7 · lost 1

Starling LM 7B Betawon 7 · lost 1

DBRX Instructwon 7 · lost 1

Mixtral 8x7B Instructwon 7 · lost 1

GPT-3.5 Turbowon 7 · lost 1

Jamba 1.5 Miniwon 7 · lost 1

Jamba 1.5 Largewon 7 · lost 1

Llama 3.1 70B Instructwon 7 · lost 1

GPT OSS 20Bwon 7 · lost 1

Llama 3.1 405B Instructwon 7 · lost 1

Gemini 2.0 Flash-Litewon 7 · lost 1

NVIDIA Nemotron 3 Super 120B A12Bwon 7 · lost 1

Qwen3 30B A3B Instructwon 7 · lost 1

Jamba Large 1.7won 6 · lost 1

Gemma 2 2B ITwon 6 · lost 1

H2o Danube3 500M Chatwon 5 · lost 1

LFM2 350Mwon 5 · lost 1

Magistral Small 1.2won 5 · lost 1

Aya 23 8Bwon 5 · lost 1

Laguna S 2.1won 5 · lost 1

SEA LION V1 7B ITwon 5 · lost 1

H2o Danube3 4B Chatwon 5 · lost 1

Ling 3.0 Flash VLwon 5 · lost 1

Jamba 1.6 Miniwon 5 · lost 1

Command R7Bwon 5 · lost 1

NexusRaven V2 13Bwon 5 · lost 1

Ling 3.0 Flashwon 5 · lost 1

SmolLM 360M Instructwon 5 · lost 1

Phi-4 Mini Instructwon 5 · lost 1

Aya 23 35Bwon 5 · lost 1

LFM2 1.2Bwon 5 · lost 1

Granite 3.0 1B A400M Instructwon 5 · lost 1

Jamba 1.6 Largewon 5 · lost 1

Jamba Instructwon 5 · lost 1

SeaLLMs V3 7B Chatwon 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

Gemma2 9B Cpt Sea Lionv3 Instructwon 5 · lost 1

GLM-5 Turbowon 5 · lost 1

Qwen 2.5 Instruct (7B)won 5 · lost 1

GPT OSS Safeguard 20Bwon 5 · lost 1

GLM-4.5 Airwon 5 · lost 1

Command R+won 7 · lost 2

Gemma 3 4B ITwon 7 · lost 2

Mercury 2won 7 · lost 2

Command Awon 7 · lost 2

Grok 4.1 Fastwon 7 · lost 2

Gemma 2B ITwon 6 · lost 2

Phi-3 Mini 128K Instructwon 6 · lost 2

Phi-3 Mini 4K Instructwon 6 · lost 2

Mistral 7B Instruct v0.2won 6 · lost 2

Granite 3.0 2B Instructwon 6 · lost 2

Llama 3.2 3B Instructwon 6 · lost 2

Granite 3.1 2B Instructwon 6 · lost 2

Phi-3 Medium 4K Instructwon 6 · lost 2

Llama 3.1 8B Instructwon 6 · lost 2

Mixtral 8x22B Instructwon 6 · lost 2

Gemma 2 9B ITwon 6 · lost 2

Gemini 1.5 Flashwon 6 · lost 2

GPT-4.1 nanowon 6 · lost 2

QwQ 32Bwon 6 · lost 2

Gemini 1.5 Prowon 6 · lost 2

Gemini 2.0 Flashwon 6 · lost 2

GPT-4.1 miniwon 6 · lost 2

GLM-4.5won 6 · lost 2

Grok 4won 6 · lost 2

Qwen3 VL 235B A22B Instructwon 6 · lost 2

DeepSeek V4 Flashwon 6 · lost 2

Grok 4.3won 6 · lost 2

Qwen3.7 Maxwon 6 · lost 2

Gemini 3.6 Flashwon 6 · lost 2

Qwen3 8Bwon 5 · lost 2

NVIDIA Nemotron 3 Ultra 550B A55Bwon 5 · lost 2

Mistral Instruct v0.3 (7B)won 4 · lost 2

OLMo 2 7B Instructwon 4 · lost 2

DeepSeek R1 Distill Qwen 7Bwon 4 · lost 2

DeepSeek R1 Distill Llama 8Bwon 4 · lost 2

Granite 3.2 8B Instructwon 4 · lost 2

Open Codestral Mambawon 4 · lost 2

Yi 1.5 9B Chatwon 4 · lost 2

Granite 3.2 2B Instructwon 4 · lost 2

Granite 3.0 3B A800M Instructwon 4 · lost 2

Apertus 8B Instructwon 4 · lost 2

Qwen2.5 32B Instructwon 4 · lost 2

LongWriter Glm4 9Bwon 4 · lost 2

Qwen2 VL 72Bwon 4 · lost 2

Qwen2 57B A14B Instructwon 4 · lost 2

Phi 3 Small 128k Instructwon 4 · lost 2

Kimi K2 Thinkingwon 4 · lost 2

EAI Llama 3.1 8B Instruct SageAlignwon 4 · lost 2

SeaLLM 7B V2won 4 · lost 2

K2 Chatwon 4 · lost 2

Krutrim 2 Instructwon 4 · lost 2

EAI SageAlign 8B LoRAwon 4 · lost 2

Gemini 2.5 Flash-Litewon 4 · lost 2

Gemini 3 Prowon 4 · lost 2

Mistral Small 3 24B Instructwon 6 · lost 3

Amazon Nova Prowon 6 · lost 3

Llama 3.3 70B Instructwon 6 · lost 3

Llama 4 Scout Instructwon 6 · lost 3

Gemma 3 12B ITwon 6 · lost 3

Gemma 3 27B ITwon 6 · lost 3

O4 Miniwon 6 · lost 3

Gemini 2.5 Flashwon 6 · lost 3

Grok 3won 6 · lost 3

DeepSeek V3.1won 6 · lost 3

Kimi K2won 6 · lost 3

DeepSeek V3.2won 6 · lost 3

GLM-4.6won 6 · lost 3

Gemini 2.5 Prowon 6 · lost 3

Gemma 4 31Bwon 6 · lost 3

Kimi K2.6won 6 · lost 3

Llama 3.2 1B Instructwon 5 · lost 3

Phi-3 Small 8K Instructwon 5 · lost 3

Granite 3.0 8B Instructwon 5 · lost 3

Granite 3.1 8B Instructwon 5 · lost 3

Llama 3.1 Tulu 3 8Bwon 5 · lost 3

Llama 3 8B Instructwon 5 · lost 3

Claude 3 Haikuwon 5 · lost 3

GPT-4won 5 · lost 3

Llama 3 70B Instructwon 5 · lost 3

GPT-4o miniwon 5 · lost 3

Qwen Maxwon 5 · lost 3

O3 Miniwon 5 · lost 3

Mistral Large 4won 5 · lost 3

MiniMax M3won 5 · lost 3

MiMo V2.6 Flashwon 5 · lost 3

Kimi K2.5won 5 · lost 3

MiMo V2.5 Prowon 5 · lost 3

GLM-5.2won 5 · lost 3

Gemini 3.5 Flashwon 5 · lost 3

Gemini 3.8 Flashwon 5 · lost 3

Claude Opus 4.6won 4 · lost 3

Amazon Nova Litewon 5 · lost 4

Llama 4 Maverick Instructwon 5 · lost 4

GPT OSS 120Bwon 5 · lost 4

Qwen3.5 35B A3Bwon 5 · lost 4

DeepSeek R1won 5 · lost 4

Gemma 4 26B A4Bwon 5 · lost 4

GPT-6 Solwon 5 · lost 4

DeepSeek V4 Prowon 5 · lost 4

GPT-5.6 Solwon 5 · lost 4

Komodo 7B Basewon 3 · lost 3

IBM Granite 4.0 Microwon 3 · lost 3

Dolphin 2.5 Mixtral 8x7bwon 3 · lost 3

Reflection Llama 3.1 70Bwon 3 · lost 3

Granite 3.1 3B A800M Instructwon 3 · lost 3

Sarvam 30Bwon 3 · lost 3

Qwen2.5 14B Instructwon 3 · lost 3

Phi 3 Medium 128k Instructwon 3 · lost 3

Smaug Llama 3 70B Instructwon 3 · lost 3

Apertus 70B Instructwon 3 · lost 3

Granite 4.0 H Microwon 3 · lost 3

Granite 4.0 H Tinywon 3 · lost 3

Phi 3.5 Mini Instructwon 3 · lost 3

Llama 3.1 Tulu 3 8B SFTwon 3 · lost 3

Llama 3.1 Tulu 3 8B DPOwon 3 · lost 3

Fugu Ultra V2won 3 · lost 3

Llama 3 8B Instruct MopeyMulewon 3 · lost 3

Qwen3 Next 80B A3B Thinkingwon 3 · lost 3

Llama 2 7B Chatwon 4 · lost 4

Llama 2 13B Chatwon 4 · lost 4

Llama 2 70B Chatwon 4 · lost 4

Qwen2 72B Instructwon 4 · lost 4

Claude 3 Sonnetwon 4 · lost 4

GPT-4 Turbowon 4 · lost 4

O1 Miniwon 4 · lost 4

Claude 3.7 Sonnetwon 4 · lost 4

O1won 4 · lost 4

GLM-5.1won 4 · lost 4

GLM-5.3 Flashwon 4 · lost 4

MiMo V2.6 Prowon 4 · lost 4

Aya Expanse 8Bwon 4 · lost 5

Amazon Nova Microwon 4 · lost 5

Phi 4won 4 · lost 5

Aya Expanse 32Bwon 4 · lost 5

Granite 4.0 H Smallwon 4 · lost 5

GPT-4owon 4 · lost 5

GPT-5 miniwon 4 · lost 5

Qwen3 235B A22B Instructwon 4 · lost 5

Claude Sonnet 4.6won 3 · lost 4

Gemma 2 27B ITwon 3 · lost 5

Llama 3.1 Nemotron 70B Instructwon 3 · lost 5

Qwen2.5 72B Instructwon 3 · lost 5

Claude 3 Opuswon 3 · lost 5

Claude 3.5 Haikuwon 3 · lost 5

MiniMax M2won 3 · lost 5

Claude 3.5 Sonnetwon 3 · lost 5

Qwen3.5 122B A10Bwon 3 · lost 5

O3won 3 · lost 5

GPT-6 Lunawon 3 · lost 5

GPT-5.6 Lunawon 3 · lost 5

Qwen3.8 Maxwon 3 · lost 5

Phi 3.5 MoE Instructwon 2 · lost 4

Llama 3.2 Vision (11B)won 2 · lost 4

Titan Text Express V1won 2 · lost 4

Llama 3 8B Instruct RRwon 2 · lost 4

Sarvam 105Bwon 2 · lost 4

Foundation Sec 8B Instructwon 2 · lost 4

Meta SecAlign 8Bwon 2 · lost 4

Mistral NeMo Minitron 8B Instructwon 2 · lost 4

GPT-5 nanowon 3 · lost 6

Claude Sonnet 4won 3 · lost 6

GPT-4.1won 3 · lost 6

GPT-5.1won 2 · lost 6

Grok 4.5won 2 · lost 6

GPT-5.6 Terrawon 2 · lost 6

Muse Spark 1.1won 2 · lost 6

Claude Haiku 4.5won 2 · lost 7

GPT-5.5won 2 · lost 7

Claude Opus 4.7won 2 · lost 7

Nova Premierwon 1 · lost 5

Llama 3.2 Vision (90B)won 1 · lost 5

Cogito 671B V2 P1won 1 · lost 5

Apriel 1.5 15B Thinkerwon 1 · lost 5

Inklingwon 1 · lost 7

Hy3won 1 · lost 7

Claude Sonnet 5won 1 · lost 7

Claude Opus 4.8won 1 · lost 7

MiniMax M2.7won 1 · lost 8

Claude Opus 4won 1 · lost 8

GPT-5won 1 · lost 8

Claude Sonnet 4.5won 1 · lost 8

GPT-5.4won 1 · lost 8

Qwen3.5 397B A17Bwon 0 · lost 8

Grok 4.7won 0 · lost 8

Grok 4.6won 0 · lost 8

Claude Opus 5won 0 · lost 8

GPT-5.2won 0 · lost 9

Claude Opus 5.5won 0 · lost 9

§ 3 · Sources

Where the numbers come from

3 publications, 8 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-11

LMArena Text 1409

Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-11

Enkrypt · Jailbreak risk 14%Enkrypt · Harmful content risk 1.1%Enkrypt · CBRN risk 28.8%Enkrypt · Toxicity risk 3.6%Enkrypt · Bias risk 60.5%Enkrypt · Insecure code risk 6.2%

Vectara Hallucination Leaderboard ↗1 measureread 2026-11-11

Vectara · Factual consistency 87.9%

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