Model comparison

DeepSeek-V3.2-Speciale vs Mistral Large

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 31.6 on the Noometry Index.

Last verified October 10, 2026. 2 shared benchmarks.

DeepSeek-V3.2-Speciale

DeepSeek

39.1

Rank #159 Reported

Mistral Large

Mistral AI

31.6

Rank #258 Confirmed

Summary

They share 2 benchmarks with published results for both. DeepSeek-V3.2-Speciale scores higher in 3 categories and Mistral Large in 0 categories; 3 gaps are clear of the uncertainty.
The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 15.4.
The biggest single-benchmark swing is SimpleBench: 52.6% for DeepSeek-V3.2-Speciale and 22.5% for Mistral Large.
DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $2 / $6 for Mistral Large.
Mistral Large accepts more context: 131K tokens versus 128K.

Side by side

DeepSeek-V3.2-Speciale and Mistral Large specifications
	DeepSeek-V3.2-Speciale	Mistral Large
Provider	DeepSeek	Mistral AI
Noometry Index	39.1	31.6
Released	2025-12-01	2024-02-26
Weights	Open	Open
Context window	128K	131K
Max output	128K	16K
Input $ / M tokens	$0.58	$2
Output $ / M tokens	$1.68	$6
Results tracked	3	51

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 39.9 (#136), Mistral Large: 33.8 (#240)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
SciCode	—	36.2%
WeirdML	46.7%	—
BigCodeBench Instruct	—	30%
LiveBench Coding	—	47.1%
LMArena Coding	—	1277
BigCodeBench Complete	—	38.3%
ALE-Bench	—	264.7
HumanEval+	—	62.2%
MBPP+	—	59.5%

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Large: 28.4 (#83)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
Berkeley Function Calling Leaderboard	—	38.4%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.1 (#65), Mistral Large: 15.4 (#305)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
SimpleBench	52.6%	22.5%
CritPt	—	0%
LiveBench Reasoning	—	43.5%
LMArena Hard Prompts	—	1257
DTBench	—	65.1%
LiveBench Data Analysis	—	50.1%
LMCA	—	16.7%
Epoch Capabilities Index	—	128.52
ForecastBench	—	57.1
LiveBench	—	48.4%

Math Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Large: 17.1 (#285)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
OTIS Mock AIME 2024-2025	—	8.5%
Omni-MATH	—	28.1%
LiveBench Math	—	42.5%
LMArena Math	—	1262
MATH Level 5	—	50.3%
FrontierMath (Feb 2025 set)	—	0.3%

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Large: 30.0 (#224)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
GPQA Diamond	—	51.3%
MMLU-Pro	—	59.9%
Confabulations	—	21.4%
Vectara Hallucination Rate	—	4.5%
GPQA (HELM)	—	43.5%
LMArena Expert	—	1232
MMLU	—	80%

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Large: 40.1 (#214)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
LMArena Non-English	—	1237
LMArena Chinese	—	1240
LMArena French	—	1324
LMArena German	—	1254
LMArena Japanese	—	1187
LMArena Korean	—	1202
LMArena Russian	—	1257
LMArena Spanish	—	1268

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Large: 68.1 (#186)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
LiveBench Instruction Following	—	67.9%
IFEval	—	87.7%
LMArena Instruction Following	—	1249

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Mistral Large: 38.3 (#194)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
LMArena Longer Query	—	1262

Writing & Preference DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 46.1 (#217), Mistral Large: 40.9 (#237)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mistral Large
EQ-Bench Creative Writing	1276	985
LMArena Text	—	1266
LMArena Creative Writing	—	1243
Short-Story Creative Writing	—	69%
WildBench	—	80.1%
LMArena Multi-Turn	—	1260
LiveBench Language	—	39.4%

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Mistral Large?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 31.6 on the Noometry Index.

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

DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Mistral Large lists at $2 and $6.

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

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 33.8 in the Noometry coding category.

Which has the bigger context window?

Mistral Large does, with 131K tokens against 128K.

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

2 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Mistral Large has 51.