Model comparison

DeepSeek-V3.2-Speciale vs Llama 4 Scout

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 27.4 on the Noometry Index. Llama 4 Scout costs 5.7× 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 4 Scout

Summary

They share 1 benchmark with published results for both. DeepSeek-V3.2-Speciale scores higher in 3 categories and Llama 4 Scout 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 9.2.
Llama 4 Scout is cheaper at $0.10 / $0.30 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.

Side by side

DeepSeek-V3.2-Speciale and Llama 4 Scout specifications
	DeepSeek-V3.2-Speciale	Llama 4 Scout
Provider	DeepSeek	Meta
Noometry Index	39.1	27.4
Released	2025-12-01	2025-04-05
Weights	Open	Open
Context window	128K	128K
Max output	128K	4K
Input $ / M tokens	$0.58	$0.10
Output $ / M tokens	$1.68	$0.30
Results tracked	3	43

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 39.9 (#136), Llama 4 Scout: 19.9 (#334)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
SWE-bench Verified (bash only)	—	9.1%
SciCode	—	17%
WeirdML	46.7%	—
LMArena Coding	—	1286
BigCodeBench Complete	—	43.1%

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Speciale: —, Llama 4 Scout: 24.4 (#109)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
Berkeley Function Calling Leaderboard	—	28.1%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.1 (#65), Llama 4 Scout: 9.2 (#339)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
ARC-AGI-2	—	0%
SimpleBench	52.6%	—
Kagi LLM Benchmark	—	36.9%
ARC-AGI-1	—	0.5%
CritPt	—	0%
LMArena Hard Prompts	—	1266
DTBench	—	57.9%
LMCA	—	12%
Epoch Capabilities Index	—	129.64
ForecastBench	—	57.5

Math Not comparable

DeepSeek-V3.2-Speciale: —, Llama 4 Scout: 18.4 (#280)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
OTIS Mock AIME 2024-2025	—	7.8%
Omni-MATH	—	37.3%
LMArena Math	—	1286
MATH Level 5	—	62.3%
FrontierMath (Feb 2025 set)	—	0%

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Llama 4 Scout: 31.8 (#208)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
GPQA Diamond	—	51.8%
MMLU-Pro	—	74.2%
Vectara Hallucination Rate	—	7.7%
GPQA (HELM)	—	50.7%
LMArena Expert	—	1236

Multimodal Not comparable

DeepSeek-V3.2-Speciale: —, Llama 4 Scout: 31.6 (#98)

Multimodal benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
LMArena Vision	—	1118
SpatialViz-Bench	—	34.2%

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Llama 4 Scout: 41.3 (#207)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
LMArena Non-English	—	1253
LMArena Chinese	—	1256
LMArena French	—	1283
LMArena German	—	1274
LMArena Japanese	—	1209
LMArena Korean	—	1207
LMArena Russian	—	1263
LMArena Spanish	—	1277

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Llama 4 Scout: 66.0 (#212)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
IFEval	—	81.8%
LMArena Instruction Following	—	1248

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Llama 4 Scout: 27.5 (#289)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
Fiction.LiveBench	—	36%
LMArena Longer Query	—	1265

Writing & Preference DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 46.1 (#217), Llama 4 Scout: 37.1 (#256)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Llama 4 Scout
EQ-Bench Creative Writing	1276	783
LMArena Text	—	1279
LMArena Creative Writing	—	1249
WildBench	—	78%
LMArena Multi-Turn	—	1281

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Llama 4 Scout?

Which is cheaper, DeepSeek-V3.2-Speciale or Llama 4 Scout?

Llama 4 Scout is cheaper. It lists at $0.10 per million input tokens and $0.30 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

Is DeepSeek-V3.2-Speciale or Llama 4 Scout better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 19.9 in the Noometry coding category.

Which has the bigger context window?

Both accept 128K tokens.

How many benchmarks do DeepSeek-V3.2-Speciale and Llama 4 Scout share?

1 benchmark has published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Llama 4 Scout has 43.