Noometry

Model comparison

DeepSeek-V3.2-Exp vs Gemini 2.5 Pro

DeepSeek-V3.2-Exp and Gemini 2.5 Pro score almost the same on the Noometry Index (44.3 vs 45.0), so choose on price, context window or the category you care about most.

Last verified . 40 shared benchmarks.

DeepSeek-V3.2-Exp DeepSeek

44.3

Rank #78 Confirmed

Gemini 2.5 Pro Google

45.0

Rank #75 Confirmed

Summary

  • They share 40 benchmarks with published results for both. DeepSeek-V3.2-Exp scores higher in 3 categories and Gemini 2.5 Pro in 6 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in long context, where Gemini 2.5 Pro leads 59.8 to 47.6.
  • The biggest single-benchmark swing is Kagi LLM Benchmark: 52.2% for DeepSeek-V3.2-Exp and 70.3% for Gemini 2.5 Pro.
  • DeepSeek-V3.2-Exp is cheaper at $0.26 / $0.38 per million input/output tokens, against $1.25 / $10 for Gemini 2.5 Pro.
  • Gemini 2.5 Pro accepts more context: 1.05M tokens versus 164K.
  • DeepSeek-V3.2-Exp has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.2-ExpGemini 2.5 Pro
ProviderDeepSeekGoogle
Noometry Index44.345.0
Released2025-09-292025-03-25
WeightsOpenProprietary
Context window164K1.05M
Max output66K66K
Input $ / M tokens$0.26$1.25
Output $ / M tokens$0.38$10
Results tracked4978

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Category by category

Coding DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 46.5 (#65), Gemini 2.5 Pro: 42.4 (#101)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
SWE-bench Verified (bash only)70%53.6%
Aider Polyglot74.2%83.1%
LMArena WebDev13621227
SciCode38.9%42.8%
WeirdML39.5%54%
LMArena Coding14541452
SWE-bench Verified—57.6%
SWE-bench Multilingual59%—
GSO—3.9%
LiveBench Coding—85.9%
CadEval—64%
ALE-Bench—785.52
AlgoTune—1.51

Agentic & Tool Use DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 32.7 (#59), Gemini 2.5 Pro: 29.2 (#88)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
Terminal-Bench39.6%32.6%
TheAgentCompany42.9%30.3%
Vending-Bench 21,034573.64
APEX-Agents21.3%—
Berkeley Function Calling Leaderboard56.7%—
GDPval—23.3%
Remote Labor Index—0.8%
τ²-bench Banking—13.7%
DeepResearch Bench—42.8%
BALROG—43.3%
LMArena Search—1142
METR Time Horizons—55.4%

Reasoning Gemini 2.5 Pro leads

DeepSeek-V3.2-Exp: 22.1 (#208), Gemini 2.5 Pro: 28.8 (#99)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
ARC-AGI-24%4.9%
Kagi LLM Benchmark52.2%70.3%
ARC-AGI-157%41%
CritPt2.9%2%
Chess Puzzles14%20%
LMArena Hard Prompts14341455
DTBench87.7%82.4%
LMCA29.1%34.8%
Epoch Capabilities Index146.27145.32
SimpleBench—62.4%
NYT Connections (extended)36.7%—
EnigmaEval—5.6%
Thematic Generalization65%—
LiveBench Reasoning—89.8%
LiveBench Data Analysis—79.9%
ForecastBench—61.3
LiveBench—82.3%

Math DeepSeek-V3.2-Exp leads

DeepSeek-V3.2-Exp: 41.7 (#87), Gemini 2.5 Pro: 32.5 (#213)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
OTIS Mock AIME 2024-202587.8%84.7%
LMArena Math14351450
FrontierMath (Feb 2025 set)22.1%14.1%
FrontierMath Tier 4 (v1)2.1%4.2%
FrontierMath (Tiers 1-3)—24.6%
FrontierMath Tier 4—0%
MathArena Final-Answer Competitions57.7%—
ProofBench8%—
Omni-MATH—41.6%
LiveBench Math—90.2%
MATH Level 5—95.9%

Knowledge Gemini 2.5 Pro leads

DeepSeek-V3.2-Exp: 51.7 (#66), Gemini 2.5 Pro: 56.0 (#46)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
GPQA Diamond83.4%85.3%
Vectara Hallucination Rate5.3%7%
LMArena Expert14361452
Humanity's Last Exam—21.6%
MMLU-Pro—86.3%
Confabulations—10.6%
GPQA (HELM)—74.9%

Multimodal Not comparable

DeepSeek-V3.2-Exp: —, Gemini 2.5 Pro: 45.2 (#18)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
LMArena Vision—1263
GeoBench—86%
VPCT—48%
LMArena Document—1421
SpatialViz-Bench—44.7%

Multilingual Gemini 2.5 Pro leads

DeepSeek-V3.2-Exp: 52.2 (#90), Gemini 2.5 Pro: 55.3 (#31)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
LMArena Non-English14091451
LMArena Chinese14611507
LMArena French14331472
LMArena German14401487
LMArena Japanese13741461
LMArena Korean13711434
LMArena Russian14241461
LMArena Spanish14401473

Instruction Following Too close to call

DeepSeek-V3.2-Exp: 74.5 (#93), Gemini 2.5 Pro: 75.0 (#75)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
LMArena Instruction Following14131437
LiveBench Instruction Following—80.6%
IFEval—84%

Long Context Gemini 2.5 Pro leads

DeepSeek-V3.2-Exp: 47.6 (#16), Gemini 2.5 Pro: 59.8 (#5)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
Fiction.LiveBench83.3%91.7%
LMArena Longer Query14281449
CL-bench13.2%—
CL-bench Life9.5%—

Writing & Preference Gemini 2.5 Pro leads

DeepSeek-V3.2-Exp: 62.4 (#77), Gemini 2.5 Pro: 63.7 (#62)

BenchmarkDeepSeek-V3.2-ExpGemini 2.5 Pro
LMArena Text14251458
LMArena Creative Writing14031454
EQ-Bench Creative Writing15151421
LMArena Multi-Turn14271453
Short-Story Creative Writing—83.8%
WildBench—85.7%
LiveBench Language—67.8%

Frequently asked questions

Is DeepSeek-V3.2-Exp better than Gemini 2.5 Pro?

DeepSeek-V3.2-Exp and Gemini 2.5 Pro score almost the same on the Noometry Index (44.3 vs 45.0), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3.2-Exp or Gemini 2.5 Pro?

DeepSeek-V3.2-Exp is cheaper. It lists at $0.26 per million input tokens and $0.38 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.

Is DeepSeek-V3.2-Exp or Gemini 2.5 Pro better for coding?

DeepSeek-V3.2-Exp scores higher on coding benchmarks: 46.5 versus 42.4 in the Noometry coding category.

Which has the bigger context window?

Gemini 2.5 Pro does, with 1.05M tokens against 164K.

How many benchmarks do DeepSeek-V3.2-Exp and Gemini 2.5 Pro share?

40 benchmarks have published results for both models. DeepSeek-V3.2-Exp has 49 scored results on Noometry and Gemini 2.5 Pro has 78.

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