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MiniMax M2.7

MiniMax · 229B · open weights

Strongest in Secure code (#6 of 270), weakest in Coding (#148 of 179). Above par in 11 of 22 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5 and Claude Fable 5.1 and ahead of Grok 4.1 Fast and DeepSeek R1.

§ 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.

Safety58.5#14/329
Secure code65.8#6/270
Fairness70#10/292
Jailbreak resistance62.7#18/268
Harm refusal56.3#43/292
Toxicity avoidance56.4#59/268
Factual grounding42.5#86/104
Reasoning55.7#37/195
Mathematics56.6#40/152
Science57.3#42/122
Human preference58.1#115/354
Human preference58.1#115/354
Knowledge49.6#118/197
Academic knowledge49#83/123
Agents49.5#135/298
Knowledge work49.2#100/208
Professional46.1#145/194
Legal47.9#108/173
Medical45.8#116/149
Finance43.7#129/162
Coding42.6#148/179
Agentic coding42.2#143/173

§ 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 MiniMax M2.7, left for the other.

Jamba 1.6 Miniwon 15 · lost 0
Jamba 1.6 Largewon 15 · lost 0
Gemini 1.5 Flashwon 16 · lost 0
GPT-4o miniwon 20 · lost 0
GPT-4.1 nanowon 21 · lost 0
Llama 4 Scout Instructwon 19 · lost 1
Magistral Small 1.2won 16 · lost 1
Command R+won 15 · lost 1
Mistral Medium 3.1won 13 · lost 1
GPT OSS 20Bwon 17 · lost 2
Gemini 1.5 Prowon 15 · lost 2
Mistral Medium 3.5won 13 · lost 2
Llama 3.3 70B Instructwon 16 · lost 3
Gemini 2.0 Flashwon 15 · lost 4
GPT OSS 120Bwon 17 · lost 5
Command Awon 16 · lost 5
O3 Miniwon 16 · lost 5
Mistral Large 3won 11 · lost 4
Gemma 4 31Bwon 13 · lost 5
GPT-4.1 miniwon 15 · lost 6
GPT-5.4 nanowon 12 · lost 5
Gemini 2.5 Flash-Litewon 11 · lost 5
GPT-5 nanowon 13 · lost 6
DeepSeek V3won 15 · lost 7
Claude Haiku 4.5won 15 · lost 7
Grok 4 Fastwon 10 · lost 5
Claude 3.5 Haikuwon 13 · lost 7
Grok 3won 13 · lost 7
GLM-4.5won 11 · lost 6
GPT-4owon 14 · lost 8
GPT-5 miniwon 13 · lost 8
Grok 4.3won 13 · lost 8
Ling 3.0 Flashwon 11 · lost 7
MiniMax M2.5won 9 · lost 6
Gemini 3.1 Flash-Litewon 10 · lost 7
Claude Sonnet 4won 12 · lost 10
Kimi K2.5won 12 · lost 10
Kimi K2 Thinkingwon 9 · lost 8
GPT-6 Lunawon 10 · lost 9
O4 Miniwon 11 · lost 10
Gemini 2.5 Flashwon 11 · lost 10
GPT-4.1won 11 · lost 10
Kimi K2won 11 · lost 10
DeepSeek R1won 11 · lost 10
Grok 4.1 Fastwon 11 · lost 10
Grok 3 Miniwon 8 · lost 8
Grok 4won 10 · lost 10
DeepSeek V3.2won 11 · lost 11
GLM-4.6won 11 · lost 11
Gemini 2.5 Prowon 11 · lost 11
O1won 9 · lost 10
MiniMax M2.1won 7 · lost 8
Claude 3.7 Sonnetwon 9 · lost 11
MiMo V2.5 Prowon 9 · lost 11
Claude 3.5 Sonnetwon 8 · lost 10
Mistral Large 4won 8 · lost 10
MiMo V2.6 Flashwon 8 · lost 10
MiMo V2.6 Prowon 8 · lost 10
Qwen3 235B A22B Instructwon 9 · lost 12
Inklingwon 9 · lost 12
GLM-5.1won 9 · lost 12
GLM-5.3 Flashwon 9 · lost 12
GLM-5.2won 9 · lost 12
Gemini 3.5 Flashwon 9 · lost 12
Qwen3.5 Flashwon 6 · lost 9
Inkling Smallwon 6 · lost 9
MiMo V2.5won 6 · lost 9
Gemini 3.5 Flash-Litewon 6 · lost 9
MiniMax M3won 8 · lost 13
DeepSeek V4 Flashwon 8 · lost 13
GPT-5.6 Lunawon 8 · lost 13
Qwen3.7 Maxwon 8 · lost 13
Gemini 3.6 Flashwon 8 · lost 13
Qwen3.8 Maxwon 8 · lost 13
Claude Sonnet 4.5won 8 · lost 14
Kimi K2.6won 8 · lost 14
DeepSeek V4 Prowon 8 · lost 14
Claude Opus 4won 7 · lost 13
O3won 7 · lost 13
Grok 4.5won 7 · lost 14
Gemini 3.8 Flashwon 7 · lost 14
GPT-5.4 miniwon 5 · lost 11
GPT-6 Solwon 6 · lost 14
Claude Sonnet 4.6won 6 · lost 14
GLM-4.7won 5 · lost 12
GPT-5.6 Terrawon 6 · lost 15
Grok 4.7won 5 · lost 13
GPT-5won 6 · lost 16
GPT-5.1won 6 · lost 16
GPT-5.4won 6 · lost 16
GPT-5.5won 6 · lost 16
GPT-5.6 Solwon 6 · lost 16
Qwen3.8 27Bwon 4 · lost 11
Qwen3.6 Pluswon 4 · lost 11
Claude Opus 4.5won 4 · lost 12
Grok 4.6won 5 · lost 16
Muse Spark 1.1won 5 · lost 16
Gemini 3.1 Prowon 4 · lost 13
Gemini 3 Prowon 4 · lost 14
Claude Opus 4.6won 4 · lost 14
GLM-5won 3 · lost 12
Gemini 3 Flashwon 3 · lost 12
DeepSeek V4.1 Flashwon 3 · lost 12
GPT-5.2won 4 · lost 17
Claude Opus 5won 4 · lost 17
Muse Spark 1.2won 2 · lost 12
Claude Opus 4.8won 3 · lost 18
Claude Opus 4.7won 3 · lost 19
GLM-5.3won 2 · lost 13
Kimi K3won 2 · lost 13
Muse Sparkwon 2 · lost 13
Claude Opus 5.5won 2 · lost 18
Claude Sonnet 5won 2 · lost 19
Gemini 4 Argonwon 1 · lost 13
GPT-6 Astrawon 1 · lost 14
Gemini 3.7 Flashwon 1 · lost 14
Claude Fable 5.1won 0 · lost 15
Claude Fable 5won 0 · lost 15

§ 3 · Sources

Where the numbers come from

6 publications, 24 figures. Every one links to the page it was read from.

LMArena Text ↗1 measureread 2026-11-10
LMArena Text 1415
GDPval-AA ↗1 measureread 2026-11-10
GDPval-AA 1016
AA-Briefcase ↗1 measureread 2026-11-10
AA-Briefcase 719
Vals.ai ↗14 measuresread 2026-11-10
Vals · Legal Research Bench 10.58%Vals · CaseLaw 60.88%Vals · LegalBench 83.98%Vals · Finance Agent 27.89%Vals · CorpFin 61.19%Vals · TaxEval 66.56%Vals · MedCode 34.44%Vals · MedScribe 79.87%Vals · SWE-bench Verified 73.8% (Mini-SWE-agent)Vals · Vibe Code Bench 11.93% (OpenHands)Vals · Code Migration 8.69%Vals · GPQA Diamond 86.62%Vals · MMLU Pro 80.43%Vals · AIME 91.04%
Enkrypt AI Safety Leaderboard ↗6 measuresread 2026-11-10
Enkrypt · Jailbreak risk 2.2%Enkrypt · Harmful content risk 2.2%Enkrypt · CBRN risk 15%Enkrypt · Toxicity risk 1.8%Enkrypt · Bias risk 45.5%Enkrypt · Insecure code risk 0.9%
Vectara · Factual consistency 87.1%

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