Model comparison

DeepSeek-V3.2-Speciale vs Gemma 2 27B

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.4 on the Noometry Index.

Last verified October 12, 2026. 0 shared benchmarks.

DeepSeek-V3.2-Speciale

DeepSeek

39.7

Rank #162 Reported

Gemma 2 27B

Google

29.4

Rank #312 Confirmed

Summary

The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.9 to 15.3.
Gemma 2 27B is cheaper at $0.65 / $0.65 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 8K.

Side by side

DeepSeek-V3.2-Speciale and Gemma 2 27B specifications
	DeepSeek-V3.2-Speciale	Gemma 2 27B
Provider	DeepSeek	Google
Noometry Index	39.7	29.4
Released	2025-12-01	2024-06-24
Weights	Open	Open
Context window	128K	8K
Max output	128K	2K
Input $ / M tokens	$0.58	$0.65
Output $ / M tokens	$1.68	$0.65
Results tracked	3	34

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Category by category

Coding DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 40.4 (#140), Gemma 2 27B: 34.1 (#246)

Coding benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
WeirdML	46.7%	—
BigCodeBench Instruct	—	42.8%
LiveBench Coding	—	36%
LMArena Coding	—	1211
BigCodeBench Complete	—	52.5%

Reasoning DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 32.9 (#73), Gemma 2 27B: 15.3 (#315)

Reasoning benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
SimpleBench	52.6%	—
LiveBench Reasoning	—	28.1%
LMArena Hard Prompts	—	1198
DTBench	—	48%
LiveBench Data Analysis	—	47.9%
LMCA	—	7.1%
Epoch Capabilities Index	—	122.08
LiveBench	—	38.2%

Math Not comparable

DeepSeek-V3.2-Speciale: —, Gemma 2 27B: 10.7 (#311)

Math benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
OTIS Mock AIME 2024-2025	—	1.4%
LiveBench Math	—	26.5%
LMArena Math	—	1212
MATH Level 5	—	27.9%

Knowledge Not comparable

DeepSeek-V3.2-Speciale: —, Gemma 2 27B: 19.0 (#280)

Knowledge benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
GPQA Diamond	—	36.5%
Confabulations	—	27.1%
LMArena Expert	—	1172
MMLU	—	75.7%

Multilingual Not comparable

DeepSeek-V3.2-Speciale: —, Gemma 2 27B: 38.6 (#226)

Multilingual benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
LMArena Non-English	—	1217
LMArena Chinese	—	1221
LMArena French	—	1247
LMArena German	—	1209
LMArena Japanese	—	1175
LMArena Korean	—	1174
LMArena Russian	—	1234
LMArena Spanish	—	1228

Instruction Following Not comparable

DeepSeek-V3.2-Speciale: —, Gemma 2 27B: 60.5 (#249)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
LiveBench Instruction Following	—	58.1%
LMArena Instruction Following	—	1206

Long Context Not comparable

DeepSeek-V3.2-Speciale: —, Gemma 2 27B: 37.3 (#218)

Long Context benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
LMArena Longer Query	—	1231

Writing & Preference DeepSeek-V3.2-Speciale leads

DeepSeek-V3.2-Speciale: 46.0 (#222), Gemma 2 27B: 44.2 (#225)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.2-Speciale	Gemma 2 27B
LMArena Text	—	1231
LMArena Creative Writing	—	1241
EQ-Bench Creative Writing	1276	—
LMArena Multi-Turn	—	1224
LiveBench Language	—	32.6%

Frequently asked questions

Is DeepSeek-V3.2-Speciale better than Gemma 2 27B?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.4 on the Noometry Index.

Which is cheaper, DeepSeek-V3.2-Speciale or Gemma 2 27B?

Gemma 2 27B is cheaper. It lists at $0.65 per million input tokens and $0.65 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

Is DeepSeek-V3.2-Speciale or Gemma 2 27B better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 34.1 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.2-Speciale does, with 128K tokens against 8K.

How many benchmarks do DeepSeek-V3.2-Speciale and Gemma 2 27B share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemma 2 27B has 34.