Noometry

Model comparison

DeepSeek-V3.2-Exp vs Gemma 2 2b IT

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 33.1 on the Noometry Index.

Last verified . 17 shared benchmarks.

DeepSeek-V3.2-Exp DeepSeek

44.3

Rank #78 Confirmed

Gemma 2 2b IT Google

33.1

Rank #248 Confirmed

Summary

  • They share 17 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 8 categories and Gemma 2 2b IT in 0 categories; 7 gaps are clear of the uncertainty.
  • The widest gap is in writing & preference, where DeepSeek-V3.2-Exp leads 62.4 to 36.5.

Side by side

DeepSeek-V3.2-ExpGemma 2 2b IT
ProviderDeepSeekGoogle
Noometry Index44.333.1
Released2025-09-29—
WeightsOpenOpen
Context window164K—
Max output66K—
Input $ / M tokens$0.26—
Output $ / M tokens$0.38—
Results tracked4917

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Category by category

Coding DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 46.5 (#65), Gemma 2 2b IT: 32.3 (#273)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Coding14541112
SWE-bench Verified (bash only)70%—
Aider Polyglot74.2%—
LMArena WebDev1362—
SWE-bench Multilingual59%—
SciCode38.9%—
WeirdML39.5%—

Agentic & Tool Use Not comparable

DeepSeek-V3.2-Exp: 32.7 (#59), Gemma 2 2b IT: —

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
Terminal-Bench39.6%—
APEX-Agents21.3%—
Berkeley Function Calling Leaderboard56.7%—
TheAgentCompany42.9%—
Vending-Bench 21,034—

Reasoning Too close to call

DeepSeek-V3.2-Exp: 22.1 (#208), Gemma 2 2b IT: 21.4 (#224)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Hard Prompts14341113
ARC-AGI-24%—
Kagi LLM Benchmark52.2%—
NYT Connections (extended)36.7%—
ARC-AGI-157%—
CritPt2.9%—
Chess Puzzles14%—
Thematic Generalization65%—
DTBench87.7%—
LMCA29.1%—
Epoch Capabilities Index146.27—

Math DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 41.7 (#87), Gemma 2 2b IT: 32.6 (#212)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Math14351135
MathArena Final-Answer Competitions57.7%—
OTIS Mock AIME 2024-202587.8%—
ProofBench8%—
FrontierMath (Feb 2025 set)22.1%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 51.7 (#66), Gemma 2 2b IT: 29.9 (#231)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Expert14361096
GPQA Diamond83.4%—
Vectara Hallucination Rate5.3%—

Multilingual DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 52.2 (#90), Gemma 2 2b IT: 32.3 (#257)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Non-English14091121
LMArena Chinese14611132
LMArena French14331157
LMArena German14401114
LMArena Japanese13741083
LMArena Korean13711055
LMArena Russian14241118
LMArena Spanish14401140

Instruction Following DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 74.5 (#93), Gemma 2 2b IT: 57.8 (#263)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Instruction Following14131118

Long Context DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 47.6 (#16), Gemma 2 2b IT: 34.3 (#250)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Longer Query14281130
Fiction.LiveBench83.3%—
CL-bench13.2%—
CL-bench Life9.5%—

Writing & Preference DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 62.4 (#77), Gemma 2 2b IT: 36.5 (#263)

BenchmarkDeepSeek-V3.2-ExpGemma 2 2b IT
LMArena Text14251156
LMArena Creative Writing14031147
LMArena Multi-Turn14271118
EQ-Bench Creative Writing1515—

Frequently asked questions

Is DeepSeek-V3.2-Exp better than Gemma 2 2b IT?

DeepSeek-V3.2-Exp is the stronger model overall, scoring 44.3 to 33.1 on the Noometry Index.

Is DeepSeek-V3.2-Exp or Gemma 2 2b IT better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 32.3 in the Noometry coding category.

How many benchmarks do DeepSeek-V3.2-Exp and Gemma 2 2b IT share?

17 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 49 scored results on Noometry and Gemma 2 2b IT has 17.

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