Model comparison

DeepSeek-V3 vs Gemini 2.5 Flash

DeepSeek-V3 and Gemini 2.5 Flash score almost the same on the Noometry Index (39.5 vs 39.3), so choose on price, context window or the category you care about most.

Last verified October 10, 2026. 38 shared benchmarks.

DeepSeek-V3

DeepSeek

39.5

Rank #166 Confirmed

Gemini 2.5 Flash

Google

39.3

Rank #170 Confirmed

Summary

They share 38 benchmarks with published results for both. DeepSeek-V3 scores higher in 4 categories and Gemini 2.5 Flash in 4 categories; 8 gaps are clear of the uncertainty.
The widest gap is in long context, where Gemini 2.5 Flash leads 47.5 to 34.0.
The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 37.8% for DeepSeek-V3 and 73.1% for Gemini 2.5 Flash.
DeepSeek-V3 is cheaper at $0.24 / $0.90 per million input/output tokens, against $0.30 / $2.50 for Gemini 2.5 Flash.
Gemini 2.5 Flash accepts more context: 1.05M tokens versus 164K.
DeepSeek-V3 has downloadable open weights; the other is API-only.

Side by side

DeepSeek-V3 and Gemini 2.5 Flash specifications
	DeepSeek-V3	Gemini 2.5 Flash
Provider	DeepSeek	Google
Noometry Index	39.5	39.3
Released	2024-12-26	2025-04-17
Weights	Open	Proprietary
Context window	164K	1.05M
Max output	164K	66K
Input $ / M tokens	$0.24	$0.30
Output $ / M tokens	$0.90	$2.50
Results tracked	60	54

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Category by category

Coding DeepSeek-V3 leads

DeepSeek-V3: 42.3 (#106), Gemini 2.5 Flash: 35.8 (#220)

Coding benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
Aider Polyglot	55.1%	55.1%
WeirdML	36.1%	41.9%
LMArena Coding	1368	1424
SWE-bench Verified (bash only)	—	28.7%
SciCode	35.8%	—
BigCodeBench Instruct	50%	—
LiveBench Coding	70.9%	—
BigCodeBench Complete	62.2%	—
ALE-Bench	—	661.88
HumanEval+	86.6%	—
MBPP+	73%	—

Agentic & Tool Use Not comparable

DeepSeek-V3: —, Gemini 2.5 Flash: 30.8 (#74)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
Terminal-Bench	—	17.1%
Berkeley Function Calling Leaderboard	—	56.2%
TheAgentCompany	—	41.1%
BALROG	—	33.5%
METR Time Horizons	49.6%	—
Vending-Bench 2	—	548.84

Reasoning DeepSeek-V3 leads

DeepSeek-V3: 20.5 (#236), Gemini 2.5 Flash: 18.1 (#286)

Reasoning benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
SimpleBench	27.2%	41.2%
Kagi LLM Benchmark	52.3%	56.8%
CritPt	0%	1.1%
LMArena Hard Prompts	1365	1422
DTBench	64.8%	76.5%
LMCA	15.5%	27.5%
Epoch Capabilities Index	135.94	143.03
ForecastBench	59.1	60.6
ARC-AGI-2	—	2.5%
ARC-AGI-1	—	33.3%
EnigmaEval	—	2.7%
LiveBench Reasoning	65.8%	—
LiveBench Data Analysis	60.9%	—
BIG-Bench Hard	87.5%	—
HellaSwag	88.9%	—
LiveBench	66.9%	—
PIQA	84.7%	—
WinoGrande	85.2%	—

Math Gemini 2.5 Flash leads

DeepSeek-V3: 32.1 (#219), Gemini 2.5 Flash: 39.9 (#98)

Math benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
OTIS Mock AIME 2024-2025	37.8%	73.1%
Omni-MATH	40.3%	38.5%
LMArena Math	1373	1415
FrontierMath (Feb 2025 set)	1.7%	4.8%
LiveBench Math	73.5%	—
MATH Level 5	75.5%	—
FrontierMath Tier 4 (v1)	—	4.2%

Knowledge DeepSeek-V3 leads

DeepSeek-V3: 37.5 (#155), Gemini 2.5 Flash: 36.4 (#168)

Knowledge benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
MMLU-Pro	72.3%	63.9%
Confabulations	26.1%	16.8%
Vectara Hallucination Rate	6.1%	7.8%
GPQA (HELM)	53.8%	39%
LMArena Expert	1351	1426
GPQA Diamond	67.6%	—
Humanity's Last Exam	—	12.1%
ARC (AI2) Challenge	95.3%	—
MMLU	87.2%	—
TriviaQA	82.9%	—

Multimodal Not comparable

DeepSeek-V3: —, Gemini 2.5 Flash: 41.8 (#32)

Multimodal benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
LMArena Vision	—	1253
GeoBench	—	76%
VPCT	—	46.2%
SpatialViz-Bench	—	36.9%

Multilingual Gemini 2.5 Flash leads

DeepSeek-V3: 48.5 (#143), Gemini 2.5 Flash: 52.3 (#88)

Multilingual benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
LMArena Non-English	1358	1409
LMArena Chinese	1391	1450
LMArena French	1385	1433
LMArena German	1374	1418
LMArena Japanese	1333	1405
LMArena Korean	1319	1385
LMArena Russian	1373	1415
LMArena Spanish	1358	1421

Instruction Following Gemini 2.5 Flash leads

DeepSeek-V3: 72.8 (#130), Gemini 2.5 Flash: 75.7 (#54)

Instruction Following benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
IFEval	83.2%	89.8%
LMArena Instruction Following	1345	1405
LiveBench Instruction Following	81.5%	—

Long Context Gemini 2.5 Flash leads

DeepSeek-V3: 34.0 (#253), Gemini 2.5 Flash: 47.5 (#17)

Long Context benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
Fiction.LiveBench	50%	77.8%
LMArena Longer Query	1352	1419

Writing & Preference DeepSeek-V3 leads

DeepSeek-V3: 57.4 (#130), Gemini 2.5 Flash: 53.8 (#157)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3	Gemini 2.5 Flash
LMArena Text	1375	1417
LMArena Creative Writing	1364	1400
Short-Story Creative Writing	77%	76.5%
EQ-Bench Creative Writing	1472	1137
WildBench	83%	81.7%
LMArena Multi-Turn	1389	1408
LiveBench Language	49.1%	—

Frequently asked questions

Is DeepSeek-V3 better than Gemini 2.5 Flash?

DeepSeek-V3 and Gemini 2.5 Flash score almost the same on the Noometry Index (39.5 vs 39.3), so choose on price, context window or the category you care about most.

Which is cheaper, DeepSeek-V3 or Gemini 2.5 Flash?

DeepSeek-V3 is cheaper. It lists at $0.24 per million input tokens and $0.90 per million output tokens; Gemini 2.5 Flash lists at $0.30 and $2.50.

Is DeepSeek-V3 or Gemini 2.5 Flash better for coding?

DeepSeek-V3 scores higher on coding benchmarks: 42.3 versus 35.8 in the Noometry coding category.

Which has the bigger context window?

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

How many benchmarks do DeepSeek-V3 and Gemini 2.5 Flash share?

38 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and Gemini 2.5 Flash has 54.