Model comparison

DeepSeek-V3.1 vs Mistral Medium 3.5

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 40.2 on the Noometry Index.

Last verified October 10, 2026. 18 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

Mistral Medium 3.5

Mistral AI

40.2

Rank #152 Confirmed

Summary

They share 18 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 4 categories and Mistral Medium 3.5 in 4 categories; 5 gaps are clear of the uncertainty.
The widest gap is in reasoning, where DeepSeek-V3.1 leads 27.9 to 17.3.
The biggest single-benchmark swing is Kagi LLM Benchmark: 53.2% for DeepSeek-V3.1 and 41.4% for Mistral Medium 3.5.
DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
Mistral Medium 3.5 accepts more context: 262K tokens versus 164K.

Side by side

DeepSeek-V3.1 and Mistral Medium 3.5 specifications
	DeepSeek-V3.1	Mistral Medium 3.5
Provider	DeepSeek	Mistral AI
Noometry Index	42.8	40.2
Released	2025-08-21	—
Weights	Open	Open
Context window	164K	262K
Max output	8K	210K
Input $ / M tokens	$0.25	$1.50
Output $ / M tokens	$0.95	$7.50
Results tracked	27	22

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Category by category

Coding DeepSeek-V3.1 leads

DeepSeek-V3.1: 40.3 (#144), Mistral Medium 3.5: 36.0 (#213)

Coding benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Coding	1417	1461
LMArena WebDev	—	1264
WeirdML	38.4%	—

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.9 (#110), Mistral Medium 3.5: 17.3 (#295)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
Kagi LLM Benchmark	53.2%	41.4%
LMArena Hard Prompts	1417	1436
Epoch Capabilities Index	139.92	141.35
SimpleBench	40%	—
NYT Connections (extended)	—	12.9%
DTBench	82.7%	—
LMCA	24.3%	—
ForecastBench	58	—

Math Too close to call

DeepSeek-V3.1: 38.9 (#122), Mistral Medium 3.5: 39.1 (#113)

Math benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Math	1420	1431

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.7 (#90), Mistral Medium 3.5: 40.0 (#126)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Expert	1405	1432
Vectara Hallucination Rate	5.5%	—

Multimodal Not comparable

DeepSeek-V3.1: —, Mistral Medium 3.5: 38.3 (#65)

Multimodal benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Vision	—	1223

Multilingual Too close to call

DeepSeek-V3.1: 51.6 (#106), Mistral Medium 3.5: 51.9 (#100)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Non-English	1400	1404
LMArena Chinese	1469	1442
LMArena French	1447	1448
LMArena German	1411	1451
LMArena Korean	1337	1385
LMArena Russian	1405	1395
LMArena Spanish	1431	1409
LMArena Japanese	1378	—

Instruction Following Too close to call

DeepSeek-V3.1: 73.9 (#110), Mistral Medium 3.5: 74.6 (#90)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Instruction Following	1400	1415

Long Context Mistral Medium 3.5 leads

DeepSeek-V3.1: 36.3 (#232), Mistral Medium 3.5: 43.2 (#103)

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Longer Query	1422	1415
Fiction.LiveBench	52.8%	—

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.3 (#98), Mistral Medium 3.5: 58.5 (#117)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Mistral Medium 3.5
LMArena Text	1420	1421
LMArena Creative Writing	1401	1374
LMArena Multi-Turn	1408	1423
EQ-Bench Creative Writing	1436	—
EQ-Bench 4	—	993

Frequently asked questions

Is DeepSeek-V3.1 better than Mistral Medium 3.5?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 40.2 on the Noometry Index.

Which is cheaper, DeepSeek-V3.1 or Mistral Medium 3.5?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is DeepSeek-V3.1 or Mistral Medium 3.5 better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 versus 36.0 in the Noometry coding category.

Which has the bigger context window?

Mistral Medium 3.5 does, with 262K tokens against 164K.

How many benchmarks do DeepSeek-V3.1 and Mistral Medium 3.5 share?

18 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Mistral Medium 3.5 has 22.