Model comparison

DeepSeek-V3.1 vs Gemini 2.5 Pro

Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 42.8 on the Noometry Index. DeepSeek-V3.1 costs 8.1× less per token, which makes it the better buy when Gemini 2.5 Pro's lead doesn't matter for your workload.

Last verified October 11, 2026. 27 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

Gemini 2.5 Pro

Google

45.0

Rank #75 Confirmed

Summary

They share 27 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 1 category and Gemini 2.5 Pro in 7 categories; 7 gaps are clear of the uncertainty.
The widest gap is in long context, where Gemini 2.5 Pro leads 59.8 to 36.3.
The biggest single-benchmark swing is Fiction.LiveBench: 52.8% for DeepSeek-V3.1 and 91.7% for Gemini 2.5 Pro.
DeepSeek-V3.1 is cheaper at $0.25 / $0.95 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-V3.1 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3.1 and Gemini 2.5 Pro specifications
	DeepSeek-V3.1	Gemini 2.5 Pro
Provider	DeepSeek	Google
Noometry Index	42.8	45.0
Released	2025-08-21	2025-03-25
Weights	Open	Proprietary
Context window	164K	1.05M
Max output	8K	66K
Input $ / M tokens	$0.25	$1.25
Output $ / M tokens	$0.95	$10
Results tracked	27	78

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Category by category

Coding Gemini 2.5 Pro leads

DeepSeek-V3.1: 40.3 (#144), Gemini 2.5 Pro: 42.4 (#101)

Coding benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
WeirdML	38.4%	54%
LMArena Coding	1417	1452
SWE-bench Verified	—	57.6%
SWE-bench Verified (bash only)	—	53.6%
Aider Polyglot	—	83.1%
LMArena WebDev	—	1227
SciCode	—	42.8%
GSO	—	3.9%
LiveBench Coding	—	85.9%
CadEval	—	64%
ALE-Bench	—	785.52
AlgoTune	—	1.51

Agentic & Tool Use Not comparable

DeepSeek-V3.1: —, Gemini 2.5 Pro: 29.2 (#88)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
Terminal-Bench	—	32.6%
GDPval	—	23.3%
Remote Labor Index	—	0.8%
TheAgentCompany	—	30.3%
τ²-bench Banking	—	13.7%
DeepResearch Bench	—	42.8%
BALROG	—	43.3%
LMArena Search	—	1142
METR Time Horizons	—	55.4%
Vending-Bench 2	—	573.64

Reasoning Too close to call

DeepSeek-V3.1: 27.9 (#110), Gemini 2.5 Pro: 28.8 (#99)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
SimpleBench	40%	62.4%
Kagi LLM Benchmark	53.2%	70.3%
LMArena Hard Prompts	1417	1455
DTBench	82.7%	82.4%
LMCA	24.3%	34.8%
Epoch Capabilities Index	139.92	145.32
ForecastBench	58	61.3
ARC-AGI-2	—	4.9%
ARC-AGI-1	—	41%
CritPt	—	2%
Chess Puzzles	—	20%
EnigmaEval	—	5.6%
LiveBench Reasoning	—	89.8%
LiveBench Data Analysis	—	79.9%
LiveBench	—	82.3%

Math DeepSeek-V3.1 leads

DeepSeek-V3.1: 38.9 (#122), Gemini 2.5 Pro: 32.5 (#213)

Math benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
LMArena Math	1420	1450
FrontierMath (Tiers 1-3)	—	24.6%
FrontierMath Tier 4	—	0%
OTIS Mock AIME 2024-2025	—	84.7%
Omni-MATH	—	41.6%
LiveBench Math	—	90.2%
MATH Level 5	—	95.9%
FrontierMath (Feb 2025 set)	—	14.1%
FrontierMath Tier 4 (v1)	—	4.2%

Knowledge Gemini 2.5 Pro leads

DeepSeek-V3.1: 43.7 (#90), Gemini 2.5 Pro: 56.0 (#46)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
Vectara Hallucination Rate	5.5%	7%
LMArena Expert	1405	1452
GPQA Diamond	—	85.3%
Humanity's Last Exam	—	21.6%
MMLU-Pro	—	86.3%
Confabulations	—	10.6%
GPQA (HELM)	—	74.9%

Multimodal Not comparable

DeepSeek-V3.1: —, Gemini 2.5 Pro: 45.2 (#18)

Multimodal benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
LMArena Vision	—	1263
GeoBench	—	86%
VPCT	—	48%
LMArena Document	—	1421
SpatialViz-Bench	—	44.7%

Multilingual Gemini 2.5 Pro leads

DeepSeek-V3.1: 51.6 (#106), Gemini 2.5 Pro: 55.3 (#31)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
LMArena Non-English	1400	1451
LMArena Chinese	1469	1507
LMArena French	1447	1472
LMArena German	1411	1487
LMArena Japanese	1378	1461
LMArena Korean	1337	1434
LMArena Russian	1405	1461
LMArena Spanish	1431	1473

Instruction Following Gemini 2.5 Pro leads

DeepSeek-V3.1: 73.9 (#110), Gemini 2.5 Pro: 75.0 (#75)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
LMArena Instruction Following	1400	1437
LiveBench Instruction Following	—	80.6%
IFEval	—	84%

Long Context Gemini 2.5 Pro leads

DeepSeek-V3.1: 36.3 (#232), Gemini 2.5 Pro: 59.8 (#5)

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
Fiction.LiveBench	52.8%	91.7%
LMArena Longer Query	1422	1449

Writing & Preference Gemini 2.5 Pro leads

DeepSeek-V3.1: 60.3 (#98), Gemini 2.5 Pro: 63.7 (#62)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Gemini 2.5 Pro
LMArena Text	1420	1458
LMArena Creative Writing	1401	1454
EQ-Bench Creative Writing	1436	1421
LMArena Multi-Turn	1408	1453
Short-Story Creative Writing	—	83.8%
WildBench	—	85.7%
LiveBench Language	—	67.8%

Frequently asked questions

Is DeepSeek-V3.1 better than Gemini 2.5 Pro?

Which is cheaper, DeepSeek-V3.1 or Gemini 2.5 Pro?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.

Is DeepSeek-V3.1 or Gemini 2.5 Pro better for coding?

Gemini 2.5 Pro scores higher on coding benchmarks: 42.4 versus 40.3 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-V3.1 and Gemini 2.5 Pro share?

27 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Gemini 2.5 Pro has 78.