The LLM benchmark aggregator.

Laguna M.1

Other

Strongest in Academic knowledge (#112 of 123), weakest in Professional (#187 of 194). Above par in 0 of 10 scopes. Among the models it meets almost everywhere, it finishes behind Claude Opus 5 and Claude Fable 5.1 and ahead of Mercury 2.5 and Mistral Small.

§ 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.

Coding40.9−25.3#161/1791/6

Agentic coding40.3−26.6#159/1731/5

Knowledge43.6−18.9#167/1971/3

Academic knowledge34.5−29.4#112/1231/1

Reasoning38.8−26.6#174/1951/5

Science26.1−37.4#122/1221/1

Professional37−25.4#187/1941/2

Medical33.2−33.3#141/1491/1

Finance35.1−27.3#152/1621/1

Legal38.6−27.3#153/1731/1

§ 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 Laguna M.1, left for the other.

Gemini 1.5 Flashwon 6 · lost 1

NVIDIA Nemotron 3.5 Lightning 30B A3Bwon 6 · lost 1

Jamba 1.6 Miniwon 5 · lost 3

Command R+won 4 · lost 3

Mistral Smallwon 4 · lost 3

Mercury 2.5won 4 · lost 3

Jamba 1.6 Largewon 4 · lost 4

Laguna XS.2won 5 · lost 5

Gemma 4 31Bwon 3 · lost 4

Mistral Medium 3.5won 4 · lost 6

GPT-4.1 nanowon 4 · lost 6

Mistral Small 3.1 24B Instructwon 3 · lost 5

Llama 4 Scout Instructwon 3 · lost 5

Magistral Small 1.2won 3 · lost 5

Magistral Medium 1.2won 3 · lost 5

Ling 3.0 Flash Finwon 2 · lost 4

GPT-4o miniwon 3 · lost 6

Claude 3.5 Haikuwon 3 · lost 6

Command Awon 3 · lost 7

Grok 4.1 Fastwon 2 · lost 8

Grok 4.3won 2 · lost 8

NVIDIA Nemotron 3 Ultra 550B A55Bwon 2 · lost 8

Mistral Large 3won 2 · lost 8

Grok 4 Fastwon 2 · lost 8

Grok 4.20won 2 · lost 8

GPT-4owon 2 · lost 8

Qwen3.6 Maxwon 1 · lost 5

Llama 3.3 70B Instructwon 1 · lost 6

Grok 2won 1 · lost 6

Mistral Large 2.1won 1 · lost 6

Mistral Medium 3.1won 1 · lost 6

Gemini 1.5 Prowon 1 · lost 7

GPT-5 nanowon 1 · lost 7

GPT OSS 20Bwon 1 · lost 7

GPT-5.4 miniwon 1 · lost 8

Claude Haiku 4.5won 1 · lost 9

GPT-5.4 nanowon 1 · lost 9

Llama 4 Maverick Instructwon 1 · lost 9

Gemini 2.0 Flashwon 1 · lost 9

Llama 3.3 Nemotron Superwon 0 · lost 6

Qwen3.6 27Bwon 0 · lost 6

Muse Spark Openwon 0 · lost 6

Step 5won 0 · lost 6

Ember 1won 0 · lost 6

Muse Spark 1.3won 0 · lost 6

GPT-6.1 Terrawon 0 · lost 6

Muse Wonderwon 0 · lost 6

MiMo V2.6 Prowon 0 · lost 7

Mistral Large 4won 0 · lost 7

Grok 4.7won 0 · lost 7

MiMo V2.6 Flashwon 0 · lost 7

Hy4won 0 · lost 7

Muse Wonder Fullwon 0 · lost 7

Gemini 4 Argonwon 0 · lost 7

Gemini 2.5 Flash-Litewon 0 · lost 8

GLM-4.5won 0 · lost 8

Claude Opus 4.1won 0 · lost 8

GPT-6 Lunawon 0 · lost 8

Claude Haiku 5.5won 0 · lost 8

Claude Sonnet 5.5won 0 · lost 8

GPT-6 Solwon 0 · lost 8

GPT-6.1 Solwon 0 · lost 8

DeepSeek V4.1 Flashwon 0 · lost 8

GPT-6 Astrawon 0 · lost 8

Claude Opus 5.5won 0 · lost 8

Claude 3.5 Sonnetwon 0 · lost 9

Muse Spark 1.2won 0 · lost 9

DeepSeek R1won 0 · lost 9

Gemini 3.1 Flash-Litewon 0 · lost 10

Ling 3.0 Flashwon 0 · lost 10

Kimi K2.5won 0 · lost 10

GPT OSS 120Bwon 0 · lost 10

GLM-4.6won 0 · lost 10

GPT-5 miniwon 0 · lost 10

Qwen3 Maxwon 0 · lost 10

Inklingwon 0 · lost 10

Qwen3.6 Pluswon 0 · lost 10

MiniMax M2.7won 0 · lost 10

Gemini 3 Flashwon 0 · lost 10

Claude Opus 4.5won 0 · lost 10

Gemini 3.5 Flash-Litewon 0 · lost 10

Qwen3.7 Maxwon 0 · lost 10

Qwen 3.5 Pluswon 0 · lost 10

Kimi K2 Thinkingwon 0 · lost 10

Gemini 3.1 Prowon 0 · lost 10

MiniMax M3won 0 · lost 10

Claude Sonnet 4.5won 0 · lost 10

MiniMax M2.5won 0 · lost 10

GPT-5.1won 0 · lost 10

MiMo V2.5won 0 · lost 10

Inkling Smallwon 0 · lost 10

DeepSeek V3won 0 · lost 10

GLM-5won 0 · lost 10

Gemini 3 Prowon 0 · lost 10

Muse Sparkwon 0 · lost 10

Qwen3.5 Flashwon 0 · lost 10

MiMo V2.5 Prowon 0 · lost 10

GPT-4.1 miniwon 0 · lost 10

Kimi K2.6won 0 · lost 10

GLM-5.1won 0 · lost 10

DeepSeek V3.2won 0 · lost 10

GLM-4.7won 0 · lost 10

Gemini 2.5 Prowon 0 · lost 10

Gemini 3.5 Flashwon 0 · lost 10

Claude Sonnet 4.6won 0 · lost 10

Gemini 3.6 Flashwon 0 · lost 10

DeepSeek V4won 0 · lost 10

GPT-5.2won 0 · lost 10

Claude Opus 4.6won 0 · lost 10

MiniMax M2.1won 0 · lost 10

GLM-5.3 Flashwon 0 · lost 10

Grok 4won 0 · lost 10

GPT-5won 0 · lost 10

Gemini 3.8 Flashwon 0 · lost 10

GPT-4.1won 0 · lost 10

Grok 3won 0 · lost 10

Qwen3.8 27Bwon 0 · lost 10

Gemini 3.7 Flashwon 0 · lost 10

Claude Sonnet 4won 0 · lost 10

GPT-5.4won 0 · lost 10

Gemini 2.5 Flashwon 0 · lost 10

Grok 3 Miniwon 0 · lost 10

Kimi K3won 0 · lost 10

Qwen3.8 Maxwon 0 · lost 10

Kimi K2won 0 · lost 10

Grok 4.5won 0 · lost 10

GLM-5.2won 0 · lost 10

O1won 0 · lost 10

DeepSeek V4 Flashwon 0 · lost 10

Claude Opus 4.7won 0 · lost 10

GPT-5.6 Lunawon 0 · lost 10

Claude 3.7 Sonnetwon 0 · lost 10

Qwen3 235B A22B Instructwon 0 · lost 10

Claude Opus 4won 0 · lost 10

Claude Sonnet 5won 0 · lost 10

Muse Spark 1.1won 0 · lost 10

O3 Miniwon 0 · lost 10

GPT-5.5won 0 · lost 10

Claude Opus 4.8won 0 · lost 10

Grok 4.6won 0 · lost 10

GPT-5.6 Terrawon 0 · lost 10

DeepSeek V4 Prowon 0 · lost 10

O4 Miniwon 0 · lost 10

GLM-5.3won 0 · lost 10

GPT-5.6 Solwon 0 · lost 10

O3won 0 · lost 10

Claude Fable 5won 0 · lost 10

Claude Fable 5.1won 0 · lost 10

Claude Opus 5won 0 · lost 10

§ 3 · Sources

Where the numbers come from

1 publication, 11 figures. Every one links to the page it was read from.

Vals.ai ↗11 measuresread 2026-11-10

Vals · Legal Research Bench 2.4%Vals · LegalBench 75.14%Vals · Finance Agent 25.03%Vals · CorpFin 58.16%Vals · TaxEval 1.64%Vals · MedCode 23.11%Vals · MedScribe 65.91%Vals · SWE-bench Verified 57.6% (Mini-SWE-agent)Vals · Vibe Code Bench 11.04% (OpenHands)Vals · GPQA Diamond 27.02%Vals · MMLU Pro 68.84%

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