The LLM benchmark aggregator.

Laguna M.1

Other

Strongest in Academic knowledge (#112 of 123), weakest in Professional (#163 of 168). Above par in 0 of 10 scopes. Among the models it meets almost everywhere, it finishes behind Claude Fable 5.1 and Claude Fable 5 and ahead of Command R Plus and Jamba 1.6 Mini.

§ 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.

Knowledge37.1−26.4#128/1381/2

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

Coding41.8−27.3#144/1651/5

Agentic coding40.6−28.1#141/1571/4

Reasoning38.8−28.1#157/1781/4

Science26.1−37.4#122/1221/1

Professional37−24.6#163/1681/1

Legal39.2−27.9#133/1511/1

Medical33.5−33.3#133/1401/1

Finance34.9−28#145/1511/1

§ 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

Nemotron 3.5 Lightningwon 4 · lost 2

Jamba 1.6 Miniwon 5 · lost 3

Command R Pluswon 4 · lost 3

Jamba 1.6 Largewon 4 · lost 4

Laguna XS.2won 5 · lost 5

GPT-4o Miniwon 4 · lost 5

Mistral Smallwon 3 · lost 4

Mercury 2.5won 3 · lost 4

Mistral Medium 3.5won 4 · lost 6

GPT-4.1 Nanowon 4 · lost 6

Mistral Small 3.1won 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

Qwen3.6 27Bwon 2 · lost 4

Claude 3.5 Haikuwon 3 · lost 6

Command Awon 3 · lost 7

Grok 4.1 Fastwon 2 · lost 8

Grok 4 Fastwon 2 · lost 8

Grok 4.3won 2 · lost 8

Gemini 3.1 Flash Litewon 2 · lost 8

Ling 3.0 Flashwon 2 · lost 8

Mistral Large 3won 2 · lost 8

GPT-4owon 2 · lost 8

Grok 4.20won 2 · lost 8

Nemotron 3 Ultrawon 2 · lost 8

Qwen3.6 Maxwon 1 · lost 5

Grok 2won 1 · lost 6

Mistral Largewon 1 · lost 6

Llama 3.3 Instruct Turbo (70B)won 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

Llama 4 Maverick Instructwon 1 · lost 9

Gemini 3.5 Flash Litewon 1 · lost 9

Llama 3.3 Nemotron Superwon 0 · lost 6

Mimo V2.6 Flashwon 0 · lost 6

Mimo V2.6 Prowon 0 · lost 6

Muse Spark 1.3won 0 · lost 6

GPT-6 Lunawon 0 · lost 7

Grok 4.7won 0 · lost 7

Hy4won 0 · lost 7

GPT-6 Solwon 0 · lost 7

GPT-6 Astrawon 0 · lost 7

Claude Opus 5.5won 0 · lost 7

Grok 3won 0 · lost 8

Gemini 2.5 Flash Litewon 0 · lost 8

GLM-4.5won 0 · lost 8

Claude Opus 4.1won 0 · lost 8

Gemma 4 31Bwon 0 · lost 8

Claude 3.5 Sonnetwon 0 · lost 9

Qwen3 235B A22B Instructwon 0 · lost 9

Grok 3 Miniwon 0 · lost 9

Muse Spark 1.2won 0 · lost 9

DeepSeek R1won 0 · lost 9

DeepSeek V4.1 Flashwon 0 · lost 9

Claude Haiku 4.5won 0 · lost 10

GPT OSS 120Bwon 0 · lost 10

GPT-5.4 Nanowon 0 · lost 10

MiniMax M3won 0 · lost 10

GPT-5 Miniwon 0 · lost 10

Kimi K2.5won 0 · lost 10

GLM-4.6won 0 · lost 10

Inklingwon 0 · lost 10

Qwen3 Maxwon 0 · lost 10

MiniMax M2.7won 0 · lost 10

Qwen3.7 Maxwon 0 · lost 10

Gemini 3 Flashwon 0 · lost 10

Qwen3.6 Pluswon 0 · lost 10

Gemini 2.0 Flashwon 0 · lost 10

Kimi K2 Thinkingwon 0 · lost 10

DeepSeek V3won 0 · lost 10

Qwen 3.5 Pluswon 0 · lost 10

Gemini 3.1 Prowon 0 · lost 10

Claude Opus 4.5won 0 · lost 10

Claude Sonnet 4.5won 0 · lost 10

MiniMax M2.5won 0 · lost 10

Qwen3.5 Flashwon 0 · lost 10

GPT-5.1won 0 · lost 10

GLM-5won 0 · lost 10

Mimo V2.5won 0 · lost 10

Inkling Smallwon 0 · lost 10

Gemini 3 Prowon 0 · lost 10

Muse Sparkwon 0 · lost 10

GPT-4.1 Miniwon 0 · lost 10

Mimo V2.5 Prowon 0 · lost 10

GLM-4.7won 0 · lost 10

DeepSeek V3.2won 0 · lost 10

GLM-5.1won 0 · lost 10

Kimi K2.6won 0 · lost 10

Gemini 2.5 Prowon 0 · lost 10

GPT-5.2won 0 · lost 10

Grok 4.5won 0 · lost 10

MiniMax M2.1won 0 · lost 10

Gemini 3.5 Flashwon 0 · lost 10

Gemini 3.6 Flashwon 0 · lost 10

DeepSeek V4won 0 · lost 10

Claude Opus 4.6won 0 · lost 10

Claude Sonnet 4.6won 0 · lost 10

Grok 4won 0 · lost 10

Gemini 3.8 Flashwon 0 · lost 10

GPT-4.1won 0 · lost 10

GPT-5won 0 · lost 10

Claude Sonnet 4won 0 · lost 10

GLM-5.3 Flashwon 0 · lost 10

Gemini 2.5 Flashwon 0 · lost 10

Qwen3.8 27Bwon 0 · lost 10

Kimi K2won 0 · lost 10

DeepSeek V4 Flashwon 0 · lost 10

GPT-5.4won 0 · lost 10

Qwen3.8 Maxwon 0 · lost 10

O1won 0 · lost 10

Gemini 3.7 Flashwon 0 · lost 10

Claude 3.7 Sonnetwon 0 · lost 10

Claude Opus 4won 0 · lost 10

GLM-5.2won 0 · lost 10

O3 Miniwon 0 · lost 10

Muse Spark 1.1won 0 · lost 10

Claude Sonnet 5won 0 · lost 10

Claude Opus 4.7won 0 · lost 10

Grok 4.6won 0 · lost 10

GPT-5.6 Lunawon 0 · lost 10

GPT-5.6 Terrawon 0 · lost 10

Claude Opus 4.8won 0 · lost 10

GPT-5.5won 0 · lost 10

DeepSeek V4 Prowon 0 · lost 10

Kimi K3won 0 · lost 10

O4 Miniwon 0 · lost 10

O3won 0 · lost 10

GLM-5.3won 0 · lost 10

GPT-5.6 Solwon 0 · lost 10

Claude Opus 5won 0 · lost 10

Claude Fable 5won 0 · lost 10

Claude Fable 5.1won 0 · lost 10

§ 3 · Sources

Where the numbers come from

1 publication, 12 figures. Every one links to the page it was read from.

Vals.ai ↗12 measuresread 2026-09-26

Vals · Legal Research Bench 2.4%Vals · LegalBench 75.14%Vals · Harvey Legal Agent Benchmark 0%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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