Model comparison

DeepSeek-V3.2-Speciale vs Mixtral 8x7B

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 27.1 on the Noometry Index.

Last verified October 10, 2026. 0 shared benchmarks.

DeepSeek-V3.2-Speciale

DeepSeek

39.7

Rank #162 Reported

Mixtral 8x7B

Mistral AI

27.1

Rank #334 Confirmed

Summary

The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 18.2.
Mixtral 8x7B is cheaper at $0.70 / $0.70 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
DeepSeek-V3.2-Speciale accepts more context: 128K tokens versus 32K.

Side by side

DeepSeek-V3.2-Speciale and Mixtral 8x7B specifications
	DeepSeek-V3.2-Speciale	Mixtral 8x7B
Provider	DeepSeek	Mistral AI
Noometry Index	39.7	27.1
Released	2025-12-01	2023-12-11
Weights	Open	Open
Context window	128K	32K
Max output	128K	32K
Input $ / M tokens	$0.58	$0.70
Output $ / M tokens	$1.68	$0.70
Results tracked	3	38

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 40.4 (#140), Mixtral 8x7B: 32.8 (#269)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
WeirdML	46.7%	—
LMArena Coding	—	1126
HumanEval+	—	39.6%
MBPP+	—	49.7%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.9 (#73), Mixtral 8x7B: 18.2 (#285)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
SimpleBench	52.6%	—
LMArena Hard Prompts	—	1115
DTBench	—	49.6%
Adversarial NLI	—	55.2%
Epoch Capabilities Index	—	118.47
ForecastBench	—	56.3
HellaSwag	—	86.7%
PIQA	—	83.6%
WinoGrande	—	77.2%

Math Not comparable

DeepSeek-V3.2-Speciale: —, Mixtral 8x7B: 18.8 (#289)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
Omni-MATH	—	10.5%
LMArena Math	—	1147
MATH Level 5	—	10%
GSM8K	—	74.4%

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Mixtral 8x7B: 11.0 (#301)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
GPQA Diamond	—	30.6%
MMLU-Pro	—	33.5%
GPQA (HELM)	—	29.6%
LMArena Expert	—	1088
ARC (AI2) Challenge	—	87.3%
MMLU	—	70.6%
OpenBookQA	—	85.8%
TriviaQA	—	82.2%

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Mixtral 8x7B: 29.6 (#266)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
LMArena Non-English	—	1077
LMArena Chinese	—	1055
LMArena French	—	1166
LMArena German	—	1114
LMArena Japanese	—	931
LMArena Korean	—	968
LMArena Russian	—	1090
LMArena Spanish	—	1111

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Mixtral 8x7B: 51.0 (#297)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
IFEval	—	57.5%
LMArena Instruction Following	—	1109

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Mixtral 8x7B: 33.4 (#260)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
LMArena Longer Query	—	1103

Writing & Preference DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 46.0 (#222), Mixtral 8x7B: 34.2 (#270)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Mixtral 8x7B
LMArena Text	—	1132
LMArena Creative Writing	—	1109
EQ-Bench Creative Writing	1276	—
WildBench	—	67.3%
LMArena Multi-Turn	—	1115

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Mixtral 8x7B?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 27.1 on the Noometry Index.

Which is cheaper, DeepSeek-V3.2-Speciale or Mixtral 8x7B?

Mixtral 8x7B is cheaper. It lists at $0.70 per million input tokens and $0.70 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

Is DeepSeek-V3.2-Speciale or Mixtral 8x7B better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 32.8 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.2-Speciale does, with 128K tokens against 32K.

How many benchmarks do DeepSeek-V3.2-Speciale and Mixtral 8x7B share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Mixtral 8x7B has 38.