Model comparison

DeepSeek-V3.2-Speciale vs Qwen3 32B

DeepSeek-V3.2-Speciale and Qwen3 32B score almost the same on the Noometry Index (39.1 vs 38.8), so choose on price, context window or the category you care about most.

Last verified October 10, 2026. 0 shared benchmarks.

DeepSeek-V3.2-Speciale

DeepSeek

39.1

Rank #159 Reported

Qwen3 32B

Alibaba (Qwen)

38.8

Rank #166 Confirmed

Summary

The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 19.6.
DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
Qwen3 32B accepts more context: 131K tokens versus 128K.

Side by side

DeepSeek-V3.2-Speciale and Qwen3 32B specifications
	DeepSeek-V3.2-Speciale	Qwen3 32B
Provider	DeepSeek	Alibaba (Qwen)
Noometry Index	39.1	38.8
Released	2025-12-01	2025-04
Weights	Open	Open
Context window	128K	131K
Max output	128K	16K
Input $ / M tokens	$0.58	$0.70
Output $ / M tokens	$1.68	$2.80
Results tracked	3	26

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 39.9 (#136), Qwen3 32B: 37.3 (#184)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
Aider Polyglot	—	40%
SciCode	—	35.4%
WeirdML	46.7%	—
LMArena Coding	—	1358

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 32B: 32.3 (#58)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
Berkeley Function Calling Leaderboard	—	48.7%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.1 (#65), Qwen3 32B: 19.6 (#233)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
SimpleBench	52.6%	—
Kagi LLM Benchmark	—	54.9%
CritPt	—	0.3%
Chess Puzzles	—	5%
LMArena Hard Prompts	—	1335
DTBench	—	67.5%
LMCA	—	17.3%
Epoch Capabilities Index	—	138.51

Math Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 32B: 37.9 (#89)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
OTIS Mock AIME 2024-2025	—	66.9%
LMArena Math	—	1399

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 32B: 40.0 (#112)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
GPQA Diamond	—	65.7%
Vectara Hallucination Rate	—	5.9%
LMArena Expert	—	1362

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 32B: 45.8 (#162)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
LMArena Non-English	—	1317
LMArena Chinese	—	1357
LMArena German	—	1341
LMArena Russian	—	1311

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 32B: 69.1 (#174)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
LMArena Instruction Following	—	1305

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 32B: 43.7 (#83)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
Fiction.LiveBench	—	74.2%
LMArena Longer Query	—	1327

Writing & Preference Qwen3 32B leads

DeepSeek-V3.2-Speciale: 46.1 (#217), Qwen3 32B: 53.1 (#158)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 32B
LMArena Text	—	1340
LMArena Creative Writing	—	1297
EQ-Bench Creative Writing	1276	—
LMArena Multi-Turn	—	1331

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Qwen3 32B?

DeepSeek-V3.2-Speciale and Qwen3 32B score almost the same on the Noometry Index (39.1 vs 38.8), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.2-Speciale or Qwen3 32B?

DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.

Is DeepSeek-V3.2-Speciale or Qwen3 32B better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 37.3 in the Noometry coding category.

Which has the bigger context window?

Qwen3 32B does, with 131K tokens against 128K.

How many benchmarks do DeepSeek-V3.2-Speciale and Qwen3 32B share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Qwen3 32B has 26.