Model comparison

DeepSeek-V3.2-Speciale vs Llama 3.2 3B

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 28.4 on the Noometry Index. Llama 3.2 3B costs 7.1× less per token, which makes it the better buy when DeepSeek-V3.2-Speciale's lead doesn't matter for your workload.

Last verified October 10, 2026. 1 shared benchmarks.

DeepSeek-V3.2-Speciale

DeepSeek

39.1

Rank #159 Reported

Llama 3.2 3B

Summary

They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 3 categories and Llama 3.2 3B in 0 categories; 3 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where DeepSeek-V3.2-Speciale leads 46.1 to 24.9.
Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
Llama 3.2 3B accepts more context: 131K tokens versus 128K.

Side by side

DeepSeek-V3.2-Speciale and Llama 3.2 3B specifications
	DeepSeek-V3.2-Speciale	Llama 3.2 3B
Provider	DeepSeek	Meta
Noometry Index	39.1	28.4
Released	2025-12-01	2024-09-24
Weights	Open	Open
Context window	128K	131K
Max output	128K	118K
Input $ / M tokens	$0.58	$0.05
Output $ / M tokens	$1.68	$0.33
Results tracked	3	18

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 39.9 (#136), Llama 3.2 3B: 27.1 (#314)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
WeirdML	46.7%	—
BigCodeBench Instruct	—	23.4%
LMArena Coding	—	1098
BigCodeBench Complete	—	28.3%

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 3B: 19.9 (#135)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
Berkeley Function Calling Leaderboard	—	21.9%
BALROG	—	10.1%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.1 (#65), Llama 3.2 3B: 20.1 (#225)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
SimpleBench	52.6%	—
LMArena Hard Prompts	—	1095

Math Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 3B: 29.9 (#213)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
LMArena Math	—	1126

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 3B: 29.1 (#232)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
LMArena Expert	—	1090

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 3B: 26.4 (#276)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
LMArena Non-English	—	1019
LMArena Chinese	—	1017
LMArena German	—	1056
LMArena Russian	—	949

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 3B: 56.3 (#270)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
LMArena Instruction Following	—	1089

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 3B: 33.4 (#256)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
LMArena Longer Query	—	1101

Writing & Preference DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 46.1 (#217), Llama 3.2 3B: 24.9 (#302)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 3B
EQ-Bench Creative Writing	1276	595
LMArena Text	—	1110
LMArena Creative Writing	—	1094
LMArena Multi-Turn	—	1105

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Llama 3.2 3B?

Which is cheaper, DeepSeek-V3.2-Speciale or Llama 3.2 3B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

Is DeepSeek-V3.2-Speciale or Llama 3.2 3B better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 27.1 in the Noometry coding category.

Which has the bigger context window?

Llama 3.2 3B does, with 131K tokens against 128K.

How many benchmarks do DeepSeek-V3.2-Speciale and Llama 3.2 3B share?

1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Llama 3.2 3B has 18.