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Magistral Medium

Mistral

Strongest in Reasoning (#113 of 147, on 1 of its 3 boards), weakest in Safety (#274 of 329). Above par in 0 of 12 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5.5 and Claude Opus 4.7 and ahead of Qwen3 30B A3B Instruct and Jamba 1.5 Large.

§ 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.

Reasoning45.5#136/195
Reasoning41.9#113/147
Core abilities37.8#193/199
General intelligence32.4#175/178
Human preference47.5#228/354
Human preference47.5#228/354
Safety45.6#274/329
Secure code48.6#169/270
Fairness45.9#172/292
Jailbreak resistance46.8#195/268
Toxicity avoidance47#215/268
Harm refusal42.6#264/292

§ 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 Magistral Medium, left for the other.

Magistral Smallwon 8 · lost 0
OLMo 7B Instructwon 7 · lost 1
DBRX Instructwon 7 · lost 1
GPT-3.5 Turbowon 8 · lost 2
Jamba Mini 1.7won 6 · lost 2
Gemma 2B ITwon 6 · lost 2
SmolLM2 1.7B Instructwon 6 · lost 2
Zephyr 7B Betawon 6 · lost 2
Gemma 7B ITwon 6 · lost 2
Nous Hermes 2 Mixtral 8x7B DPOwon 6 · lost 2
Mixtral 8x7B Instructwon 6 · lost 2
Command R+won 7 · lost 3
Grok Build 0.1won 5 · lost 3
Qwen1.5 14B Chatwon 5 · lost 3
Jamba 1.5 Largewon 5 · lost 3
Qwen3 30B A3B Instructwon 5 · lost 3
Llama 3.2 1B Instructwon 4 · lost 4
Mistral 7B Instruct v0.2won 4 · lost 4
Llama 3.2 3B Instructwon 4 · lost 4
Granite 3.1 2B Instructwon 4 · lost 4
Gemma 2 2B ITwon 4 · lost 4
Granite 3.1 8B Instructwon 4 · lost 4
Llama 3.1 8B Instructwon 4 · lost 4
Jamba 1.5 Miniwon 4 · lost 4
Gemma 2 9B ITwon 4 · lost 4
Amazon Nova Prowon 4 · lost 4
Grok 3won 6 · lost 6
DeepSeek V3won 5 · lost 7
Gemma 4 31Bwon 5 · lost 7
Llama 3.3 70B Instructwon 4 · lost 6
Grok 4.1 Fastwon 4 · lost 6
Phi-3 Mini 128K Instructwon 3 · lost 5
Llama 2 13B Chatwon 3 · lost 5
Phi-3 Mini 4K Instructwon 3 · lost 5
Granite 3.0 2B Instructwon 3 · lost 5
Llama 2 70B Chatwon 3 · lost 5
Phi-3 Small 8K Instructwon 3 · lost 5
Granite 3.0 8B Instructwon 3 · lost 5
DeepSeek LLM 67B Chatwon 3 · lost 5
Phi-3 Medium 4K Instructwon 3 · lost 5
Llama 3.1 Tulu 3 8Bwon 3 · lost 5
Aya Expanse 8Bwon 3 · lost 5
Llama 3 8B Instructwon 3 · lost 5
Mixtral 8x22B Instructwon 3 · lost 5
Amazon Nova Microwon 3 · lost 5
Amazon Nova Litewon 3 · lost 5
Aya Expanse 32Bwon 3 · lost 5
Mistral Small 3 24B Instructwon 3 · lost 5
GPT-4won 3 · lost 5
Llama 3.1 70B Instructwon 3 · lost 5
Llama 3.1 Nemotron 70B Instructwon 3 · lost 5
MiMo V2.6 Flashwon 4 · lost 7
Kimi K2won 4 · lost 8
DeepSeek R1won 4 · lost 8
Claude 3 Haikuwon 3 · lost 7
Llama 3 70B Instructwon 3 · lost 7
Gemma 3 4B ITwon 3 · lost 7
Llama 3.1 405B Instructwon 3 · lost 7
Gemini 1.5 Prowon 3 · lost 7
Grok 4.3won 3 · lost 7
Command Awon 3 · lost 8
Kimi K2.7 Codewon 2 · lost 6
Llama 2 7B Chatwon 2 · lost 6
Starling LM 7B Betawon 2 · lost 6
Phi 4won 2 · lost 6
Qwen2 72B Instructwon 2 · lost 6
Claude 3 Sonnetwon 2 · lost 6
Granite 4.0 H Smallwon 2 · lost 6
Gemma 2 27B ITwon 2 · lost 6
Qwen2.5 72B Instructwon 2 · lost 6
QwQ 32Bwon 2 · lost 6
Gemini 2.0 Flash-Litewon 2 · lost 6
NVIDIA Nemotron 3 Super 120B A12Bwon 2 · lost 6
Gemma 4 26B A4Bwon 2 · lost 6
Llama 4 Maverick Instructwon 3 · lost 9
GPT OSS 120Bwon 3 · lost 9
Gemini 2.0 Flashwon 3 · lost 9
Gemini 2.5 Flashwon 3 · lost 9
Grok 4won 3 · lost 9
DeepSeek V4 Flashwon 3 · lost 9
Gemini 1.5 Flashwon 2 · lost 7
Claude 3.5 Haikuwon 2 · lost 7
Claude 3 Opuswon 2 · lost 8
GPT-4 Turbowon 2 · lost 8
GPT-4owon 2 · lost 8
O1 Miniwon 2 · lost 8
Claude 3.7 Sonnetwon 2 · lost 8
GPT OSS 20Bwon 2 · lost 9
Llama 4 Scout Instructwon 2 · lost 9
GPT-4.1 nanowon 2 · lost 9
GLM-4.5won 2 · lost 9
GLM-4.6won 2 · lost 9
GPT-4o miniwon 2 · lost 10
MiniMax M2won 2 · lost 10
GPT-4.1won 2 · lost 10
Qwen3 235B A22B Instructwon 2 · lost 10
NVIDIA Nemotron 3 Ultra 550B A55Bwon 2 · lost 10
MiniMax M3won 2 · lost 10
Gemini 2.5 Prowon 2 · lost 10
GLM-5.3 Flashwon 2 · lost 10
GLM-5.2won 2 · lost 10
Gemma 3 12B ITwon 1 · lost 7
Mercury 2won 1 · lost 7
Qwen3 VL 235B A22B Instructwon 1 · lost 7
MiMo V2.5 Prowon 1 · lost 8
O3 Miniwon 1 · lost 9
Claude 3.5 Sonnetwon 1 · lost 9
Claude Haiku 4.5won 1 · lost 9
Kimi K2.6won 1 · lost 9
Claude Opus 4.6won 1 · lost 9
GPT-4.1 miniwon 1 · lost 10
GPT-6 Solwon 1 · lost 10
Qwen3.7 Maxwon 1 · lost 10
Gemini 3.5 Flashwon 1 · lost 10
Gemini 3.6 Flashwon 1 · lost 10
DeepSeek V3.1won 1 · lost 11
Mistral Large 4won 1 · lost 11
DeepSeek V3.2won 1 · lost 11
Kimi K2.5won 1 · lost 11
Claude Sonnet 4.5won 1 · lost 11
DeepSeek V4 Prowon 1 · lost 11
GPT-5.4won 1 · lost 11
GPT-5.6 Solwon 1 · lost 11
Nova Premierwon 0 · lost 8
Qwen Maxwon 0 · lost 8
Gemini 2.5 Flash-Litewon 0 · lost 8
Qwen3.5 35B A3Bwon 0 · lost 8
Qwen3.5 27Bwon 0 · lost 8
Qwen3.5 122B A10Bwon 0 · lost 8
Hy3won 0 · lost 8
Grok 3 Miniwon 0 · lost 9
Gemma 3 27B ITwon 0 · lost 9
MiniMax M2.7won 0 · lost 9
Claude Sonnet 4.6won 0 · lost 9
Gemini 3 Prowon 0 · lost 9
Kimi K2 Thinkingwon 0 · lost 10
O1won 0 · lost 10
Qwen3.5 397B A17Bwon 0 · lost 10
GPT-5.1won 0 · lost 10
GLM-5.1won 0 · lost 10
Muse Spark 1.1won 0 · lost 10
Claude Sonnet 5won 0 · lost 11
Claude Opus 5won 0 · lost 11
Gemini 3.8 Flashwon 0 · lost 11
GPT-5 nanowon 0 · lost 12
GPT-5 miniwon 0 · lost 12
O4 Miniwon 0 · lost 12
Claude Sonnet 4won 0 · lost 12
Claude Opus 4won 0 · lost 12
O3won 0 · lost 12
GPT-5won 0 · lost 12
GPT-5.2won 0 · lost 12
GPT-6 Lunawon 0 · lost 12
Grok 4.7won 0 · lost 12
Inklingwon 0 · lost 12
GPT-5.6 Lunawon 0 · lost 12
Grok 4.6won 0 · lost 12
Grok 4.5won 0 · lost 12
GPT-5.6 Terrawon 0 · lost 12
MiMo V2.6 Prowon 0 · lost 12
GPT-5.5won 0 · lost 12
Claude Opus 4.8won 0 · lost 12
Qwen3.8 Maxwon 0 · lost 12
Claude Opus 4.7won 0 · lost 12
Claude Opus 5.5won 0 · lost 12

§ 3 · Sources

Where the numbers come from

4 publications, 9 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1305
ARC-AGI-2 ↗1 measureread 2026-11-10
ARC-AGI-2 0%
Kagi LLM Benchmark ↗1 measureread 2026-11-10
Kagi LLM Benchmark 16.2%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 15.5%Enkrypt · Harmful content risk 66.7%Enkrypt · CBRN risk 16.8%Enkrypt · Toxicity risk 8.2%Enkrypt · Bias risk 84.2%Enkrypt · Insecure code risk 36%

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