The LLM benchmark aggregator.

Meta SecAlign 8B

Meta · 8B

Strongest in Harm refusal (#7 of 290, on 1 of its 2 boards), weakest in Fairness (#161 of 290). Above par in 5 of 6 scopes. Among the models it meets almost everywhere, it finishes behind Claude 3 Opus and Claude 3.5 Sonnet and ahead of Claude Opus 4 and GPT-4o.

§ 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.

Safety56.9−4.5#26/3271/3

Harm refusal60.1−1.4#7/2901/2

Jailbreak resistance62.9−2.1#12/2661/1

Toxicity avoidance56.6−2.4#50/2661/1

Secure code58.6−7.6#77/2681/1

Fairness46.2−23.8#161/2901/2

§ 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 Meta SecAlign 8B, left for the other.

Gemini 3.6 Flashwon 5 · lost 0

Command R7Bwon 5 · lost 0

Granite 3.2 8B Instructwon 5 · lost 0

Jamba 1.6 Largewon 5 · lost 0

Qwen Maxwon 5 · lost 0

OLMoE 1B-7B Instructwon 6 · lost 0

SmolLM 1.7B Instructwon 6 · lost 0

DBRX Instructwon 6 · lost 0

H2o Danube3 500M Chatwon 6 · lost 0

SmolLM2 1.7B Instructwon 6 · lost 0

Grok 4.1 Fastwon 6 · lost 0

Qwen3 30B A3B Instructwon 6 · lost 0

Laguna Xs 2.1won 6 · lost 0

RakutenAI 7B Instructwon 6 · lost 0

Falcon Mamba 7B Instructwon 6 · lost 0

Nous Hermes 2 Mixtral 8x7B DPOwon 6 · lost 0

CodeLlama 7B Instructwon 6 · lost 0

Qwen2.5 0.5B Instructwon 6 · lost 0

Magistral Smallwon 6 · lost 0

OLMo 2 7B Instructwon 6 · lost 0

Gemma 2B ITwon 6 · lost 0

Mixtral 8x7B Instructwon 6 · lost 0

Aya 23 8Bwon 6 · lost 0

Laguna S 2.1won 6 · lost 0

GPT-3.5 Turbowon 6 · lost 0

DeepSeek R1 Distill Qwen 7Bwon 6 · lost 0

DeepSeek R1 Distill Llama 8Bwon 6 · lost 0

H2o Danube3 4B Chatwon 6 · lost 0

Ling 3.0 Flash VLwon 6 · lost 0

MiMo V2.6 Flashwon 6 · lost 0

Zephyr 7B Betawon 6 · lost 0

Magistral Mediumwon 6 · lost 0

Jamba 1.6 Miniwon 6 · lost 0

Command R+won 6 · lost 0

DeepSeek V4 Flashwon 6 · lost 0

Command Awon 6 · lost 0

Ling 3.0 Flashwon 6 · lost 0

Jamba 1.5 Largewon 6 · lost 0

Gemma 2 9B ITwon 6 · lost 0

Qwen3 8Bwon 6 · lost 0

DeepSeek LLM 67B Chatwon 6 · lost 0

Mistral 7B Instruct v0.2won 6 · lost 0

GLM-4.6won 6 · lost 0

Mimo V2.6 Pro Ultraspeedwon 6 · lost 0

Phi-4 Mini Instructwon 6 · lost 0

Grok 4.3won 6 · lost 0

Qwen2.5 3B Instructwon 6 · lost 0

Granite 3.0 1B A400M Instructwon 6 · lost 0

QwQ 32Bwon 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

WizardLM 2.8x22Bwon 6 · lost 0

Llama 3.2 3B Instructwon 6 · lost 0

Llama 4 Scout Instructwon 6 · lost 0

Llama 3.3 70B Instructwon 6 · lost 0

Gemma 3 4B ITwon 6 · lost 0

Gemma2 9B Cpt Sea Lionv3 Instructwon 6 · lost 0

DeepSeek V4 Prowon 6 · lost 0

Qwen2.5 32B Instructwon 6 · lost 0

Qwen2.5 14B Instruct 1Mwon 6 · lost 0

Qwen2 VL 72Bwon 6 · lost 0

Phi-3 Medium 4K Instructwon 6 · lost 0

Sarvam 30Bwon 6 · lost 0

Qwen2.5 14B Instructwon 6 · lost 0

Phi 3 Medium 128k Instructwon 6 · lost 0

Phi 3 Small 128k Instructwon 6 · lost 0

Granite 3.0 8B Instructwon 6 · lost 0

MiMo V2.6 Prowon 6 · lost 0

Llama 3 8B Instructwon 6 · lost 0

Gemma 3 12B ITwon 6 · lost 0

Phi-3 Mini 128K Instructwon 6 · lost 0

Phi 3.5 Mini Instructwon 6 · lost 0

Llama 3.1 Tulu 3 8B SFTwon 6 · lost 0

Phi-3 Mini 4K Instructwon 6 · lost 0

Amazon Nova Prowon 6 · lost 0

Krutrim 2 Instructwon 6 · lost 0

Llama 3.1 Tulu 3 8Bwon 6 · lost 0

GPT-4won 6 · lost 0

Amazon Nova Microwon 6 · lost 0

Amazon Nova Litewon 6 · lost 0

Titan Text Express V1won 6 · lost 0

Mistral Instruct v0.1 (7B)won 5 · lost 1

OLMo 7B Instructwon 5 · lost 1

RakutenAI 7B Chatwon 5 · lost 1

PowerMoE 3Bwon 5 · lost 1

Phi 2won 5 · lost 1

Gemma 7B ITwon 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

Mistral Instruct v0.3 (7B)won 5 · lost 1

Qwen2 7B Instructwon 5 · lost 1

Jamba Mini 1.7won 5 · lost 1

Grok 4won 5 · lost 1

Magistral Small 1.2won 5 · lost 1

Grok 3won 5 · lost 1

Falcon H1 0.5B Instructwon 5 · lost 1

SEA LION V1 7B ITwon 5 · lost 1

Grok Build 0.1won 5 · lost 1

Qwen1.5 14B Chatwon 5 · lost 1

DeepSeek R1won 5 · lost 1

Llama 3.1 70B Instructwon 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

GLM-5.2won 5 · lost 1

NVIDIA Nemotron 3 Ultra 550B A55Bwon 5 · lost 1

Jamba 1.5 Miniwon 5 · lost 1

Open Codestral Mambawon 5 · lost 1

DeepSeek V3won 5 · lost 1

Aya 23 35Bwon 5 · lost 1

LFM2 1.2Bwon 5 · lost 1

NVIDIA Nemotron 3 Super 120B A12Bwon 5 · lost 1

MiniMax M3won 5 · lost 1

Gemma 4 E2Bwon 5 · lost 1

Mixtral 8x22B Instructwon 5 · lost 1

GLM-4.5won 5 · lost 1

Yi 1.5 9B Chatwon 5 · lost 1

Sarvam 1won 5 · lost 1

Gemma 4 E4Bwon 5 · lost 1

Komodo 7B Basewon 5 · lost 1

Mistral Small 3 24B Instructwon 5 · lost 1

DeepSeek V3.2won 5 · lost 1

Granite 3.1 2B Instructwon 5 · lost 1

Kimi K2.7 Codewon 5 · lost 1

IBM Granite 4.0 Microwon 5 · lost 1

Gemma 4 12Bwon 5 · lost 1

Hunyuan A13B Instructwon 5 · lost 1

MiMo V2.5 Prowon 5 · lost 1

DeepSeek V3.1won 5 · lost 1

Granite 3.2 2B Instructwon 5 · lost 1

Gemini 2.0 Flash-Litewon 5 · lost 1

Granite 3.0 3B A800M Instructwon 5 · lost 1

Llama 3.1 8B Instructwon 5 · lost 1

Gemma 4 31Bwon 5 · lost 1

Gemini 1.5 Prowon 5 · lost 1

Granite 3.0 2B Instructwon 5 · lost 1

Llama 3.1 405B Instructwon 5 · lost 1

Reflection Llama 3.1 70Bwon 5 · lost 1

GLM-5.3 Flashwon 5 · lost 1

Gemini 2.5 Prowon 5 · lost 1

Llama 3.2 1B Instructwon 5 · lost 1

Gemma 4 26B A4Bwon 5 · lost 1

LongWriter Glm4 9Bwon 5 · lost 1

GLM-5 Turbowon 5 · lost 1

Granite 3.1 3B A800M Instructwon 5 · lost 1

Qwen 2.5 Instruct (7B)won 5 · lost 1

Granite 3.1 8B Instructwon 5 · lost 1

Claude 3 Haikuwon 5 · lost 1

Gemini 2.0 Flashwon 5 · lost 1

Gemma 3 27B ITwon 5 · lost 1

Qwen2 57B A14B Instructwon 5 · lost 1

GPT-5.6 Astrawon 5 · lost 1

Kimi K2 Thinkingwon 5 · lost 1

EAI Llama 3.1 8B Instruct SageAlignwon 5 · lost 1

SeaLLM 7B V2won 5 · lost 1

Llama 4 Maverick Instructwon 5 · lost 1

Granite 4.0 H Microwon 5 · lost 1

GPT-6 Solwon 5 · lost 1

Granite 4.0 H Tinywon 5 · lost 1

Phi-3 Small 8K Instructwon 5 · lost 1

K2 Chatwon 5 · lost 1

GPT-4.1 nanowon 5 · lost 1

GPT-4o miniwon 5 · lost 1

Llama 3.1 Tulu 3 8B DPOwon 5 · lost 1

EAI SageAlign 8B LoRAwon 5 · lost 1

Phi 3.5 MoE Instructwon 5 · lost 1

Aya Expanse 8Bwon 5 · lost 1

Llama 3.2 Vision (11B)won 5 · lost 1

Internlm2 Chat 20Bwon 5 · lost 1

Llama 2 13B Chatwon 5 · lost 1

Llama 2 70B Chatwon 5 · lost 1

GPT-5.4won 5 · lost 1

O3 Miniwon 5 · lost 1

Llama 3 8B Instruct MopeyMulewon 5 · lost 1

Llama 3.2 Vision (90B)won 5 · lost 1

Qwen2.5 72B Instructwon 5 · lost 1

Kimi K2.5won 4 · lost 1

Mistral Large 4won 4 · lost 1

Gemini 1.5 Flashwon 4 · lost 1

Aya Expanse 32Bwon 4 · lost 1

Sarvam 105Bwon 4 · lost 1

Claude Opus 4.6won 3 · lost 1

Claude Sonnet 4.6won 3 · lost 1

Gemini 3.5 Flashwon 4 · lost 2

Kimi K2.6won 4 · lost 2

Qwen3.7 Maxwon 4 · lost 2

Gemma 2 2B ITwon 4 · lost 2

Fuguwon 4 · lost 2

Starling LM 7B Betawon 4 · lost 2

Dolphin 2.5 Mixtral 8x7bwon 4 · lost 2

Mercury 2won 4 · lost 2

GPT OSS 20Bwon 4 · lost 2

Apertus 8B Instructwon 4 · lost 2

Gemini 2.5 Flashwon 4 · lost 2

Qwen3 VL 235B A22B Instructwon 4 · lost 2

Smaug Llama 3 70B Instructwon 4 · lost 2

Kimi K2won 4 · lost 2

GPT OSS Safeguard 20Bwon 4 · lost 2

Gemini 3.8 Flashwon 4 · lost 2

Apertus 70B Instructwon 4 · lost 2

Llama 3 70B Instructwon 4 · lost 2

GPT-5.6 Solwon 4 · lost 2

Qwen3.8 Maxwon 4 · lost 2

GLM-5.1won 4 · lost 2

GPT-4.1 miniwon 4 · lost 2

Qwen3.5 27Bwon 4 · lost 2

GPT-6 Lunawon 4 · lost 2

O4 Miniwon 4 · lost 2

Qwen3.5 122B A10Bwon 4 · lost 2

GPT-5.6 Lunawon 4 · lost 2

Qwen3 235B A22B Instructwon 4 · lost 2

GPT OSS 120Bwon 4 · lost 2

Llama 3.1 Nemotron 70B Instructwon 4 · lost 2

Llama 3 8B Instruct RRwon 4 · lost 2

Nova Premierwon 4 · lost 2

Fugu Ultra V2won 4 · lost 2

Granite 4.0 H Smallwon 4 · lost 2

Llama 2 7B Chatwon 4 · lost 2

Grok 4.5won 4 · lost 2

GPT-5.5won 4 · lost 2

Qwen2 72B Instructwon 4 · lost 2

Claude Haiku 4.5won 4 · lost 2

GPT-4.1won 4 · lost 2

GPT-5.6 Terrawon 4 · lost 2

Claude Sonnet 4.5won 4 · lost 2

Foundation Sec 8B Instructwon 4 · lost 2

O1 Miniwon 4 · lost 2

Qwen3.5 397B A17Bwon 4 · lost 2

Qwen3.5 35B A3Bwon 3 · lost 2

GPT-4owon 3 · lost 2

Claude Opus 4won 3 · lost 2

Claude 3.7 Sonnetwon 3 · lost 3

Cogito 671B V2 P1won 3 · lost 3

Gemma 2 27B ITwon 3 · lost 3

Claude Sonnet 4won 3 · lost 3

GPT-4 Turbowon 3 · lost 3

GPT-5.1won 3 · lost 3

Claude Opus 5won 3 · lost 3

GPT-5.2won 3 · lost 3

Phi 4won 3 · lost 3

Grok 4.6won 3 · lost 3

GPT-5 miniwon 3 · lost 3

MiniMax M2.7won 3 · lost 3

GPT-5won 3 · lost 3

Claude Opus 5.5won 3 · lost 3

Muse Spark 1.1won 3 · lost 3

Claude Opus 4.8won 3 · lost 3

Claude 3 Sonnetwon 2 · lost 3

O3won 2 · lost 3

Claude Opus 4.7won 2 · lost 4

Apriel 1.5 15B Thinkerwon 2 · lost 4

Mistral NeMo Minitron 8B Instructwon 2 · lost 4

O1won 2 · lost 4

MiniMax M2won 2 · lost 4

Claude 3.5 Haikuwon 2 · lost 4

Inklingwon 2 · lost 4

Grok 4.7won 2 · lost 4

Claude Sonnet 5won 1 · lost 4

GPT-5 nanowon 1 · lost 5

Hy3won 1 · lost 5

Claude 3.5 Sonnetwon 1 · lost 5

Claude 3 Opuswon 0 · lost 6

§ 3 · Sources

Where the numbers come from

1 publication, 6 figures. Every one links to the page it was read from.

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

Enkrypt · Jailbreak risk 2%Enkrypt · Harmful content risk 5.6%Enkrypt · CBRN risk 2.8%Enkrypt · Toxicity risk 1.6%Enkrypt · Bias risk 83.7%Enkrypt · Insecure code risk 15.6%

Badge

[![PublicAI Index](https://publicai.io/model-index/badge?model=meta-secalign-8b)](https://publicai.io/model-index/m/meta-secalign-8b)