Model comparison

DeepSeek-V3.1-Terminus vs Gemma 3 12B

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 31.8 on the Noometry Index. Gemma 3 12B costs 6.3× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.

Last verified October 10, 2026. 14 shared benchmarks.

DeepSeek-V3.1-Terminus

DeepSeek

42.6

Rank #96 Confirmed

Gemma 3 12B

Google

31.8

Rank #255 Confirmed

Summary

They share 14 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 7 categories and Gemma 3 12B in 0 categories; 7 gaps are clear of the uncertainty.
The widest gap is in math, where DeepSeek-V3.1-Terminus leads 35.7 to 21.0.
The biggest single-benchmark swing is DTBench: 81.3% for DeepSeek-V3.1-Terminus and 48.8% for Gemma 3 12B.
Gemma 3 12B is cheaper at $0.05 / $0.15 per million input/output tokens, against $0.30 / $1 for DeepSeek-V3.1-Terminus.
DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 131K.

Side by side

DeepSeek-V3.1-Terminus and Gemma 3 12B specifications
	DeepSeek-V3.1-Terminus	Gemma 3 12B
Provider	DeepSeek	Google
Noometry Index	42.6	31.8
Released	2025-09-22	2025-03-12
Weights	Open	Open
Context window	164K	131K
Max output	66K	8K
Input $ / M tokens	$0.30	$0.05
Output $ / M tokens	$1	$0.15
Results tracked	16	24

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Category by category

Coding DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 41.5 (#114), Gemma 3 12B: 31.2 (#276)

Coding benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
SciCode	40.6%	17.4%
LMArena Coding	1426	1281
ALE-Bench	745.17	—

Agentic & Tool Use Not comparable

DeepSeek-V3.1-Terminus: —, Gemma 3 12B: 25.3 (#101)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
Berkeley Function Calling Leaderboard	—	30.4%

Reasoning DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 25.7 (#126), Gemma 3 12B: 15.2 (#307)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
CritPt	1.7%	0%
LMArena Hard Prompts	1427	1309
DTBench	81.3%	48.8%
LMCA	28.6%	4.5%
Kagi LLM Benchmark	57.4%	—
Chess Puzzles	—	0%
Epoch Capabilities Index	—	123.49

Math DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 35.7 (#138), Gemma 3 12B: 21.0 (#273)

Math benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
LMArena Math	1402	1307
OTIS Mock AIME 2024-2025	—	16.7%

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, Gemma 3 12B: 26.5 (#250)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
GPQA Diamond	—	39.5%
Vectara Hallucination Rate	—	4.4%
LMArena Expert	—	1248

Multimodal Not comparable

DeepSeek-V3.1-Terminus: —, Gemma 3 12B: —

Multimodal benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
MindCube	—	46.7%

Multilingual DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 52.3 (#87), Gemma 3 12B: 45.9 (#160)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
LMArena Non-English	1407	1318
LMArena Russian	1434	1335
LMArena German	—	1370

Instruction Following DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 74.4 (#96), Gemma 3 12B: 68.8 (#179)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
LMArena Instruction Following	1406	1299

Long Context DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 43.5 (#88), Gemma 3 12B: 40.0 (#157)

Long Context benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
LMArena Longer Query	1426	1317

Writing & Preference DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 61.3 (#87), Gemma 3 12B: 47.7 (#205)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Gemma 3 12B
LMArena Text	1420	1334
LMArena Creative Writing	1404	1331
LMArena Multi-Turn	1411	1334
EQ-Bench Creative Writing	—	1126

Frequently asked questions

Is DeepSeek-V3.1-Terminus better than Gemma 3 12B?

Which is cheaper, DeepSeek-V3.1-Terminus or Gemma 3 12B?

Gemma 3 12B is cheaper. It lists at $0.05 per million input tokens and $0.15 per million output tokens; DeepSeek-V3.1-Terminus lists at $0.30 and $1.

Is DeepSeek-V3.1-Terminus or Gemma 3 12B better for coding?

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 31.2 in the Noometry coding category.

Which has the bigger context window?

DeepSeek-V3.1-Terminus does, with 164K tokens against 131K.

How many benchmarks do DeepSeek-V3.1-Terminus and Gemma 3 12B share?

14 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Gemma 3 12B has 24.