Model comparison

DeepSeek-V3.1 vs Laguna M.1

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 32.5 on the Noometry Index.

Last verified October 11, 2026. 0 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

Laguna M.1

Poolside

32.5

Rank #256 Reported

Summary

The widest gap is in math, where DeepSeek-V3.1 leads 38.9 to 21.1.
Laguna M.1 accepts more context: 262K tokens versus 164K.

Side by side

DeepSeek-V3.1 and Laguna M.1 specifications
	DeepSeek-V3.1	Laguna M.1
Provider	DeepSeek	Poolside
Noometry Index	42.8	32.5
Released	2025-08-21	2026-04-28
Weights	Open	Open
Context window	164K	262K
Max output	8K	33K
Input $ / M tokens	$0.25	—
Output $ / M tokens	$0.95	—
Results tracked	27	3

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Category by category

Coding DeepSeek-V3.1 leads

DeepSeek-V3.1: 40.3 (#144), Laguna M.1: 36.6 (#204)

Coding benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
LMArena WebDev	—	1349
WeirdML	38.4%	—
LMArena Coding	1417	—

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.9 (#110), Laguna M.1: 23.1 (#184)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
SimpleBench	40%	—
Kagi LLM Benchmark	53.2%	—
LMArena Hard Prompts	1417	—
DTBench	82.7%	—
LMCA	24.3%	—
Surface Evolver Bench	—	15.6%
Epoch Capabilities Index	139.92	—
ForecastBench	58	—

Math DeepSeek-V3.1 leads

DeepSeek-V3.1: 38.9 (#122), Laguna M.1: 21.1 (#283)

Math benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
ProofBench	—	0%
LMArena Math	1420	—

Knowledge Not comparable

DeepSeek-V3.1: 43.7 (#90), Laguna M.1: —

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
Vectara Hallucination Rate	5.5%	—
LMArena Expert	1405	—

Multilingual Not comparable

DeepSeek-V3.1: 51.6 (#106), Laguna M.1: —

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
LMArena Non-English	1400	—
LMArena Chinese	1469	—
LMArena French	1447	—
LMArena German	1411	—
LMArena Japanese	1378	—
LMArena Korean	1337	—
LMArena Russian	1405	—
LMArena Spanish	1431	—

Instruction Following Not comparable

DeepSeek-V3.1: 73.9 (#110), Laguna M.1: —

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
LMArena Instruction Following	1400	—

Long Context Not comparable

DeepSeek-V3.1: 36.3 (#232), Laguna M.1: —

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
Fiction.LiveBench	52.8%	—
LMArena Longer Query	1422	—

Writing & Preference Not comparable

DeepSeek-V3.1: 60.3 (#98), Laguna M.1: —

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Laguna M.1
LMArena Text	1420	—
LMArena Creative Writing	1401	—
EQ-Bench Creative Writing	1436	—
LMArena Multi-Turn	1408	—

Frequently asked questions

Is DeepSeek-V3.1 better than Laguna M.1?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 32.5 on the Noometry Index.

Is DeepSeek-V3.1 or Laguna M.1 better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 versus 36.6 in the Noometry coding category.

Which has the bigger context window?

Laguna M.1 does, with 262K tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and Laguna M.1 share?

0 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Laguna M.1 has 3.