Model comparison

DeepSeek-V3.1 vs Mistral Medium 3.1

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 31.5 on the Noometry Index.

Last verified October 10, 2026. 1 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.2

Rank #106 Confirmed

Mistral Medium 3.1

Mistral AI

31.5

Rank #260 Reported

Summary

They share 1 benchmark with published results for both. DeepSeek-V3.1 scores higher in 2 categories and Mistral Medium 3.1 in 0 categories; 2 gaps are clear of the uncertainty.
The widest gap is in reasoning, where DeepSeek-V3.1 leads 27.3 to 10.1.
DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $0.40 / $2 for Mistral Medium 3.1.
DeepSeek-V3.1 accepts more context: 164K tokens versus 131K.
DeepSeek-V3.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1 and Mistral Medium 3.1 specifications
	DeepSeek-V3.1	Mistral Medium 3.1
Provider	DeepSeek	Mistral AI
Noometry Index	42.2	31.5
Released	2025-08-21	—
Weights	Open	Proprietary
Context window	164K	131K
Max output	8K	105K
Input $ / M tokens	$0.25	$0.40
Output $ / M tokens	$0.95	$2
Results tracked	27	3

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Category by category

Coding Not comparable

DeepSeek-V3.1: 39.8 (#140), Mistral Medium 3.1: —

Coding benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
WeirdML	38.4%	—
LMArena Coding	1417	—

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.3 (#109), Mistral Medium 3.1: 10.1 (#336)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
SimpleBench	40%	—
Kagi LLM Benchmark	53.2%	—
NYT Connections (extended)	—	6.5%
Thematic Generalization	—	20.3%
LMArena Hard Prompts	1417	—
DTBench	82.7%	—
LMCA	24.3%	—
Epoch Capabilities Index	139.92	—
ForecastBench	58	—

Math Not comparable

DeepSeek-V3.1: 36.1 (#125), Mistral Medium 3.1: —

Math benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
LMArena Math	1420	—

Knowledge Not comparable

DeepSeek-V3.1: 43.0 (#86), Mistral Medium 3.1: —

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
Vectara Hallucination Rate	5.5%	—
LMArena Expert	1403	—

Multilingual Not comparable

DeepSeek-V3.1: 51.8 (#100), Mistral Medium 3.1: —

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
LMArena Non-English	1400	—
LMArena Chinese	1470	—
LMArena French	1447	—
LMArena German	1412	—
LMArena Japanese	1374	—
LMArena Korean	1337	—
LMArena Russian	1405	—
LMArena Spanish	1429	—

Instruction Following Not comparable

DeepSeek-V3.1: 74.1 (#105), Mistral Medium 3.1: —

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
LMArena Instruction Following	1400	—

Long Context Not comparable

DeepSeek-V3.1: 36.3 (#227), Mistral Medium 3.1: —

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
Fiction.LiveBench	52.8%	—
LMArena Longer Query	1422	—

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.5 (#93), Mistral Medium 3.1: 55.6 (#140)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.1
EQ-Bench Creative Writing	1436	1476
LMArena Text	1420	—
LMArena Creative Writing	1401	—
LMArena Multi-Turn	1408	—

Frequently asked questions

Is DeepSeek-V3.1 better than Mistral Medium 3.1?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 31.5 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1 or Mistral Medium 3.1?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Mistral Medium 3.1 lists at $0.40 and $2.

Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 131K.

How many benchmarks do DeepSeek-V3.1 and Mistral Medium 3.1 share?

1 benchmark has published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Mistral Medium 3.1 has 3.