Model comparison

DeepSeek-V3.2-Speciale vs Qwen3 14B

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 35.0 on the Noometry Index.

Last verified October 10, 2026. 0 shared benchmarks.

DeepSeek-V3.2-Speciale

DeepSeek

39.1

Rank #159 Reported

Qwen3 14B

Alibaba (Qwen)

35.0

Rank #222 Confirmed

Summary

The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 18.1.
Qwen3 14B is cheaper at $0.35 / $1.40 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
Qwen3 14B accepts more context: 131K tokens versus 128K.

Side by side

DeepSeek-V3.2-Speciale and Qwen3 14B specifications
	DeepSeek-V3.2-Speciale	Qwen3 14B
Provider	DeepSeek	Alibaba (Qwen)
Noometry Index	39.1	35.0
Released	2025-12-01	2025-04
Weights	Open	Open
Context window	128K	131K
Max output	128K	8K
Input $ / M tokens	$0.58	$0.35
Output $ / M tokens	$1.68	$1.40
Results tracked	3	12

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 39.9 (#136), Qwen3 14B: 36.7 (#191)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 14B
SciCode	—	31.6%
WeirdML	46.7%	—

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 14B: 29.4 (#78)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 14B
Berkeley Function Calling Leaderboard	—	41%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.1 (#65), Qwen3 14B: 18.1 (#272)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 14B
SimpleBench	52.6%	—
Kagi LLM Benchmark	—	49.1%
CritPt	—	0%
Chess Puzzles	—	4%
DTBench	—	64%
LMCA	—	18.2%
Epoch Capabilities Index	—	138.23

Math Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 14B: 37.0 (#102)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 14B
OTIS Mock AIME 2024-2025	—	66.4%

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 14B: 39.2 (#124)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 14B
GPQA Diamond	—	63.8%
Vectara Hallucination Rate	—	5.4%

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Qwen3 14B: 38.0 (#201)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 14B
Fiction.LiveBench	—	62.5%

Writing & Preference Not comparable

DeepSeek-V3.2-Speciale: 46.1 (#217), Qwen3 14B: —

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Qwen3 14B
EQ-Bench Creative Writing	1276	—

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Qwen3 14B?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 35.0 on the Noometry Index.

Which is cheaper, DeepSeek-V3.2-Speciale or Qwen3 14B?

Qwen3 14B is cheaper. It lists at $0.35 per million input tokens and $1.40 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

Is DeepSeek-V3.2-Speciale or Qwen3 14B better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 36.7 in the Noometry coding category.

Which has the bigger context window?

Qwen3 14B does, with 131K tokens against 128K.

How many benchmarks do DeepSeek-V3.2-Speciale and Qwen3 14B share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Qwen3 14B has 12.