Model comparison

DeepSeek-R1 vs Gemini 2.5 Pro

Gemini 2.5 Pro is the stronger model overall, scoring 45.0 to 42.3 on the Noometry Index. DeepSeek-R1 costs 3.8× 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 10, 2026. 52 shared benchmarks.

DeepSeek-R1

DeepSeek

42.3

Rank #115 Confirmed

Gemini 2.5 Pro

Google

45.0

Rank #75 Confirmed

Summary

They share 52 benchmarks with published results for both. DeepSeek-R1 scores higher in 3 categories and Gemini 2.5 Pro in 6 categories; 9 gaps are clear of the uncertainty.
The widest gap is in long context, where Gemini 2.5 Pro leads 59.8 to 45.4.
The biggest single-benchmark swing is SimpleBench: 40.8% for DeepSeek-R1 and 62.4% for Gemini 2.5 Pro.
DeepSeek-R1 is cheaper at $0.50 / $2.15 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.

Side by side

DeepSeek-R1 and Gemini 2.5 Pro specifications
	DeepSeek-R1	Gemini 2.5 Pro
Provider	DeepSeek	Google
Noometry Index	42.3	45.0
Released	2025-01-20	2025-03-25
Weights	Proprietary	Proprietary
Context window	164K	1.05M
Max output	64K	66K
Input $ / M tokens	$0.50	$1.25
Output $ / M tokens	$2.15	$10
Results tracked	52	78

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Category by category

Coding DeepSeek-R1 leads

DeepSeek-R1: 46.3 (#68), Gemini 2.5 Pro: 42.4 (#101)

Coding benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
Aider Polyglot	71.4%	83.1%
SciCode	35.7%	42.8%
WeirdML	41.6%	54%
LiveBench Coding	66.7%	85.9%
LMArena Coding	1427	1452
ALE-Bench	804.12	785.52
AlgoTune	1.7	1.51
SWE-bench Verified	—	57.6%
SWE-bench Verified (bash only)	—	53.6%
LMArena WebDev	—	1227
GSO	—	3.9%
CadEval	—	64%

Agentic & Tool Use DeepSeek-R1 leads

DeepSeek-R1: 30.7 (#75), Gemini 2.5 Pro: 29.2 (#88)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
DeepResearch Bench	35.1%	42.8%
BALROG	34.9%	43.3%
METR Time Horizons	53.8%	55.4%
Terminal-Bench	—	32.6%
GDPval	—	23.3%
Remote Labor Index	—	0.8%
TheAgentCompany	—	30.3%
τ²-bench Banking	—	13.7%
LMArena Search	—	1142
Vending-Bench 2	—	573.64

Reasoning Gemini 2.5 Pro leads

DeepSeek-R1: 18.6 (#278), Gemini 2.5 Pro: 28.8 (#99)

Reasoning benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
ARC-AGI-2	1.3%	4.9%
SimpleBench	40.8%	62.4%
Kagi LLM Benchmark	69.4%	70.3%
ARC-AGI-1	21.2%	41%
CritPt	1.1%	2%
LiveBench Reasoning	83.2%	89.8%
LMArena Hard Prompts	1416	1455
LiveBench Data Analysis	69.8%	79.9%
Epoch Capabilities Index	141.29	145.32
ForecastBench	60	61.3
LiveBench	71.6%	82.3%
Chess Puzzles	—	20%
EnigmaEval	—	5.6%
DTBench	—	82.4%
LMCA	—	34.8%

Math DeepSeek-R1 leads

DeepSeek-R1: 43.8 (#79), Gemini 2.5 Pro: 32.5 (#213)

Math benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
OTIS Mock AIME 2024-2025	66.4%	84.7%
Omni-MATH	42.4%	41.6%
LiveBench Math	80.7%	90.2%
LMArena Math	1400	1450
MATH Level 5	96.6%	95.9%
FrontierMath (Tiers 1-3)	—	24.6%
FrontierMath Tier 4	—	0%
FrontierMath (Feb 2025 set)	—	14.1%
FrontierMath Tier 4 (v1)	—	4.2%

Knowledge Gemini 2.5 Pro leads

DeepSeek-R1: 44.5 (#87), Gemini 2.5 Pro: 56.0 (#46)

Knowledge benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
GPQA Diamond	76.3%	85.3%
MMLU-Pro	79.3%	86.3%
Confabulations	12.7%	10.6%
Vectara Hallucination Rate	11.3%	7%
GPQA (HELM)	66.6%	74.9%
LMArena Expert	1394	1452
Humanity's Last Exam	—	21.6%

Multimodal Not comparable

DeepSeek-R1: —, Gemini 2.5 Pro: 45.2 (#18)

Multimodal benchmarks
Benchmark	DeepSeek-R1	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-R1: 52.4 (#85), Gemini 2.5 Pro: 55.3 (#31)

Multilingual benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
LMArena Non-English	1412	1451
LMArena Chinese	1442	1507
LMArena French	1417	1472
LMArena German	1404	1487
LMArena Japanese	1391	1461
LMArena Korean	1360	1434
LMArena Russian	1423	1461
LMArena Spanish	1411	1473

Instruction Following Gemini 2.5 Pro leads

DeepSeek-R1: 72.0 (#143), Gemini 2.5 Pro: 75.0 (#75)

Instruction Following benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
LiveBench Instruction Following	80.5%	80.6%
IFEval	78.4%	84%
LMArena Instruction Following	1382	1437

Long Context Gemini 2.5 Pro leads

DeepSeek-R1: 45.4 (#36), Gemini 2.5 Pro: 59.8 (#5)

Long Context benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
Fiction.LiveBench	75%	91.7%
LMArena Longer Query	1391	1449

Writing & Preference Gemini 2.5 Pro leads

DeepSeek-R1: 61.4 (#88), Gemini 2.5 Pro: 63.7 (#62)

Writing & Preference benchmarks
Benchmark	DeepSeek-R1	Gemini 2.5 Pro
LMArena Text	1428	1458
LMArena Creative Writing	1405	1454
Short-Story Creative Writing	83%	83.8%
EQ-Bench Creative Writing	1500	1421
WildBench	82.8%	85.7%
LMArena Multi-Turn	1405	1453
LiveBench Language	48.5%	67.8%

Frequently asked questions

Is DeepSeek-R1 better than Gemini 2.5 Pro?

Which is cheaper, DeepSeek-R1 or Gemini 2.5 Pro?

DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Gemini 2.5 Pro lists at $1.25 and $10.

Is DeepSeek-R1 or Gemini 2.5 Pro better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 46.3 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-R1 and Gemini 2.5 Pro share?

52 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Gemini 2.5 Pro has 78.