Model comparison

DeepSeek-V3.2-Speciale vs Llama 3.2 1B

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 19.9 on the Noometry Index. Llama 3.2 1B costs 12× 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 1B

Summary

They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 3 categories and Llama 3.2 1B 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 21.4.
Llama 3.2 1B is cheaper at $0.027 / $0.20 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 60K.

Side by side

DeepSeek-V3.2-Speciale and Llama 3.2 1B specifications
	DeepSeek-V3.2-Speciale	Llama 3.2 1B
Provider	DeepSeek	Meta
Noometry Index	39.1	19.9
Released	2025-12-01	2024-09-24
Weights	Open	Open
Context window	128K	60K
Max output	128K	54K
Input $ / M tokens	$0.58	$0.027
Output $ / M tokens	$1.68	$0.20
Results tracked	3	22

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 39.9 (#136), Llama 3.2 1B: 20.6 (#333)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
WeirdML	46.7%	—
BigCodeBench Instruct	—	8.2%
LMArena Coding	—	1071
BigCodeBench Complete	—	11.3%

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 1B: 14.5 (#142)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
Berkeley Function Calling Leaderboard	—	10.8%
BALROG	—	6.6%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.1 (#65), Llama 3.2 1B: 15.6 (#304)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
SimpleBench	52.6%	—
Chess Puzzles	—	0%
LMArena Hard Prompts	—	1044
Epoch Capabilities Index	—	101.95

Math Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 1B: 9.7 (#308)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
OTIS Mock AIME 2024-2025	—	0.6%
LMArena Math	—	1086

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 1B: 7.2 (#307)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
GPQA Diamond	—	23.9%
LMArena Expert	—	1007

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 1B: 23.9 (#287)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
LMArena Non-English	—	973
LMArena Chinese	—	958
LMArena German	—	1014
LMArena Russian	—	941

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 1B: 52.6 (#285)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
LMArena Instruction Following	—	1031

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Llama 3.2 1B: 31.9 (#269)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
LMArena Longer Query	—	1050

Writing & Preference DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 46.1 (#217), Llama 3.2 1B: 21.4 (#305)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 3.2 1B
EQ-Bench Creative Writing	1276	200
LMArena Text	—	1055
LMArena Creative Writing	—	1033
LMArena Multi-Turn	—	1030

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Llama 3.2 1B?

Which is cheaper, DeepSeek-V3.2-Speciale or Llama 3.2 1B?

Llama 3.2 1B is cheaper. It lists at $0.027 per million input tokens and $0.20 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

Is DeepSeek-V3.2-Speciale or Llama 3.2 1B better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 20.6 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.2-Speciale does, with 128K tokens against 60K.

How many benchmarks do DeepSeek-V3.2-Speciale and Llama 3.2 1B share?

1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Llama 3.2 1B has 22.