Model comparison

DeepSeek-V3.2-Speciale vs Mistral Medium 3.5

DeepSeek-V3.2-Speciale and Mistral Medium 3.5 score almost the same on the Noometry Index (39.1 vs 39.6), so choose on price, context window or the category you care about most.

Last verified October 10, 2026. 0 shared benchmarks.

DeepSeek-V3.2-Speciale

DeepSeek

39.1

Rank #159 Reported

Mistral Medium 3.5

Mistral AI

39.6

Rank #151 Confirmed

Summary

The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 16.6.
DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 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 128K.

Side by side

DeepSeek-V3.2-Speciale and Mistral Medium 3.5 specifications
	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
Provider	DeepSeek	Mistral AI
Noometry Index	39.1	39.6
Released	2025-12-01	—
Weights	Open	Open
Context window	128K	262K
Max output	128K	210K
Input $ / M tokens	$0.58	$1.50
Output $ / M tokens	$1.68	$7.50
Results tracked	3	22

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 39.9 (#136), Mistral Medium 3.5: 35.7 (#208)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena WebDev	—	1263
WeirdML	46.7%	—
LMArena Coding	—	1461

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.1 (#65), Mistral Medium 3.5: 16.6 (#290)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
SimpleBench	52.6%	—
Kagi LLM Benchmark	—	41.4%
NYT Connections (extended)	—	12.9%
LMArena Hard Prompts	—	1436
Epoch Capabilities Index	—	141.42

Math Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Medium 3.5: 36.4 (#113)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena Math	—	1432

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Medium 3.5: 39.3 (#123)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena Expert	—	1431

Multimodal Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Medium 3.5: 37.6 (#64)

Multimodal benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena Vision	—	1222

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Medium 3.5: 52.1 (#93)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena Non-English	—	1405
LMArena Chinese	—	1443
LMArena French	—	1448
LMArena German	—	1453
LMArena Korean	—	1387
LMArena Russian	—	1396
LMArena Spanish	—	1406

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Medium 3.5: 74.7 (#87)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena Instruction Following	—	1414

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Medium 3.5: 43.2 (#101)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena Longer Query	—	1414

Writing & Preference Mistral Medium 3.5 leads

DeepSeek-V3.2-Speciale: 46.1 (#217), Mistral Medium 3.5: 58.6 (#113)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Medium 3.5
LMArena Text	—	1421
LMArena Creative Writing	—	1372
EQ-Bench Creative Writing	1276	—
EQ-Bench 4	—	993
LMArena Multi-Turn	—	1423

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Mistral Medium 3.5?

DeepSeek-V3.2-Speciale and Mistral Medium 3.5 score almost the same on the Noometry Index (39.1 vs 39.6), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.2-Speciale or Mistral Medium 3.5?

DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is DeepSeek-V3.2-Speciale or Mistral Medium 3.5 better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 35.7 in the Noometry coding category.

Which has the bigger context window?

Mistral Medium 3.5 does, with 262K tokens against 128K.

How many benchmarks do DeepSeek-V3.2-Speciale and Mistral Medium 3.5 share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Mistral Medium 3.5 has 22.