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DeepSeek V3 vs Gemini 2.5 Flash

DeepSeek V3 costs 2.6x less per output token than Gemini 2.5 Flash ($0.9594 vs $2.50 per million). Updated October 22, 2026; 10 benchmarks have a result for both.

DeepSeek V3DeepSeek
Coding
No data
Overall
No data
Output $/M
$0.9594
6
Gemini 2.5 FlashGoogle
Coding
No data
Overall
34.3
Output $/M
$2.50
4
vs boards won of 10 shared

DeepSeek V3 or Gemini 2.5 Flash: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick DeepSeek V3 for output tokens 2.6x cheaper ($0.9594 vs $2.50 per million) and work measured by Kagi LLM Benchmark or Design Arena: SVG, where it leads.

Shared results
10
DeepSeek V3 only
4
Gemini 2.5 Flash only
63
Like-for-like categories
3 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
DeepSeek V3 not benchmarked, Gemini 2.5 Flash not benchmarked.
Widest category
General, 13.1 points apart on average over 2 shared benchmarks.
Widest single gap
DTBench: DeepSeek V3 62.7% against Gemini 2.5 Flash 76.5%, 13.9 points apart on a 0 to 100 scale.
Output price
DeepSeek V3 $0.9594 against Gemini 2.5 Flash $2.50 per million output tokens, 2.6x apart.
Context window
DeepSeek V3 takes 164K tokens, Gemini 2.5 Flash 1.05M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryDeepSeek V3BarsGemini 2.5 FlashTies
Reasoning01
Web design61
General02
All shared boards64
CodingDirectional onlySix of these boards feed the Vibe Coding Index8 boards, none shared
Coding benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
Aider polyglot70.2%Not measuredOnly DeepSeek V3 measured
SWE-bench VerifiedNot measured28.7%Only Gemini 2.5 Flash measured
SWE-bench Lite30.7%Not measuredOnly DeepSeek V3 measured
LiveCodeBench (Artificial Analysis run)Not measured69.5%Only Gemini 2.5 Flash measured
Terminal-Bench Hard (Artificial Analysis run)Not measured13.6%Only Gemini 2.5 Flash measured
Terminal-BenchNot measured17.1%Only Gemini 2.5 Flash measured
LMArena Text: codingNot measured1423Only Gemini 2.5 Flash measured
LMArena Text: software and ITNot measured1425Only Gemini 2.5 Flash measured
Neither model has a result on the other 31 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
AA Intelligence IndexNot measured15.5Only Gemini 2.5 Flash measured
Epoch Capabilities IndexNot measured142.9Only Gemini 2.5 Flash measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Agentic work benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
τ²-Bench TelecomNot measured31.6%Only Gemini 2.5 Flash measured
BALROGNot measured33.5%Only Gemini 2.5 Flash measured
Vending-Bench 2Not measured$549Only Gemini 2.5 Flash measured
Berkeley Function Calling Leaderboard (BFCL)Not measured56.2%Only Gemini 2.5 Flash measured
BrowseComp-PlusNot measured39.9%Only Gemini 2.5 Flash measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
GPQA Diamond (Artificial Analysis run)Not measured79.0%Only Gemini 2.5 Flash measured
Humanity's Last Exam (Artificial Analysis run)Not measured12.1%Only Gemini 2.5 Flash measured
GPQA Diamond (Epoch AI run)71.2%Not measuredOnly DeepSeek V3 measured
ARC-AGINot measured33.3%Only Gemini 2.5 Flash measured
ARC-AGI-2Not measured2.5%Only Gemini 2.5 Flash measured
SimpleBenchNot measured41.2%Only Gemini 2.5 Flash measured
LMArena Text: hard promptsNot measured1422Only Gemini 2.5 Flash measured
LMArena Text: expertNot measured1426Only Gemini 2.5 Flash measured
LMArena Text: hard prompts in EnglishNot measured1420Only Gemini 2.5 Flash measured
LMArena Vision: diagramsNot measured1245Only Gemini 2.5 Flash measured
LMArena Vision: homeworkNot measured1244Only Gemini 2.5 Flash measured
Kagi LLM Benchmark52.3%56.8%Gemini 2.5 Flash
Neither model has a result on the other 10 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
AA Math IndexNot measured73.3Only Gemini 2.5 Flash measured
AIME 2025 (Artificial Analysis run)Not measured73.3%Only Gemini 2.5 Flash measured
OTIS Mock AIME48.9%Not measuredOnly DeepSeek V3 measured
LMArena Text: mathNot measured1411Only Gemini 2.5 Flash measured
LMArena Text: mathematical workNot measured1422Only Gemini 2.5 Flash measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Knowledge benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
MedCode (Vals AI)Not measured40.4%Only Gemini 2.5 Flash measured
MMLU Pro (Artificial Analysis run)Not measured83.2%Only Gemini 2.5 Flash measured
LMArena Text: scienceNot measured1433Only Gemini 2.5 Flash measured
LMArena Text: medicine and healthcareNot measured1428Only Gemini 2.5 Flash measured
LMArena Text: legal and governmentNot measured1430Only Gemini 2.5 Flash measured
LMArena Text: business and financeNot measured1404Only Gemini 2.5 Flash measured
FACTS Benchmark SuiteNot measured47.2%Only Gemini 2.5 Flash measured
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index61
Web design benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
Design Arena: websites11201074DeepSeek V3
Design Arena: UI components10901002DeepSeek V3
Design Arena: game dev10531004DeepSeek V3
Design Arena: data viz10891060DeepSeek V3
Design Arena: 3D10861020DeepSeek V3
Design Arena: all code categories11081059DeepSeek V3
Design Arena: SVG9761020Gemini 2.5 Flash
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
General benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
SAGE (Vals AI)Not measured44.8%Only Gemini 2.5 Flash measured
MedScribe (Vals AI)Not measured83.0%Only Gemini 2.5 Flash measured
IFBenchNot measured50.3%Only Gemini 2.5 Flash measured
Long context reasoning (AA-LCR)Not measured65.3%Only Gemini 2.5 Flash measured
DTBench62.7%76.5%Gemini 2.5 Flash
LMCA15.2%27.5%Gemini 2.5 Flash
LMArena TextNot measured1417Only Gemini 2.5 Flash measured
LMArena Text: instruction followingNot measured1405Only Gemini 2.5 Flash measured
LMArena Text: creative writingNot measured1400Only Gemini 2.5 Flash measured
LMArena VisionNot measured1235Only Gemini 2.5 Flash measured
LMArena Text: EnglishNot measured1418Only Gemini 2.5 Flash measured
LMArena Text: non-EnglishNot measured1409Only Gemini 2.5 Flash measured
LMArena Text: ChineseNot measured1449Only Gemini 2.5 Flash measured
LMArena Text: GermanNot measured1417Only Gemini 2.5 Flash measured
LMArena Text: JapaneseNot measured1396Only Gemini 2.5 Flash measured
LMArena Text: KoreanNot measured1385Only Gemini 2.5 Flash measured
LMArena Text: FrenchNot measured1432Only Gemini 2.5 Flash measured
LMArena Text: SpanishNot measured1422Only Gemini 2.5 Flash measured
LMArena Text: RussianNot measured1415Only Gemini 2.5 Flash measured
LMArena Text: PolishNot measured1413Only Gemini 2.5 Flash measured
LMArena Text: multi-turnNot measured1408Only Gemini 2.5 Flash measured
LMArena Text: longer queriesNot measured1419Only Gemini 2.5 Flash measured
LMArena Text: writing and languageNot measured1405Only Gemini 2.5 Flash measured
LMArena Text: entertainment and mediaNot measured1393Only Gemini 2.5 Flash measured
LMArena Vision: EnglishNot measured1239Only Gemini 2.5 Flash measured
LMArena Vision: ChineseNot measured1284Only Gemini 2.5 Flash measured
LMArena Vision: reading textNot measured1237Only Gemini 2.5 Flash measured
LMArena Vision: humorNot measured1225Only Gemini 2.5 Flash measured
LMArena Vision: captioningNot measured1277Only Gemini 2.5 Flash measured
LMArena Vision: recognizing thingsNot measured1252Only Gemini 2.5 Flash measured
LMArena Vision: creative writingNot measured1241Only Gemini 2.5 Flash measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3 and Gemini 2.5 Flash
BenchmarkDeepSeek V3Gemini 2.5 FlashLeader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

DeepSeek V3$0.0008Fits in one request
Gemini 2.5 Flash$0.0015Fits in one request

DeepSeek V3 costs less

Repository review

50K input + 3K output tokens

DeepSeek V3$0.017Fits in one request
Gemini 2.5 Flash$0.022Fits in one request

DeepSeek V3 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3$0.067Exceeds the context window
Gemini 2.5 Flash$0.085Fits in one request

DeepSeek V3 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of DeepSeek V3 and Gemini 2.5 Flash
SpecificationDeepSeek V3Google Gemini 2.5 Flash
MakerDeepSeekGoogle
WeightsOpen weightsNo public weights listed
ReleasedDecember 26, 2024June 17, 2025
Context window164K1.05M
Input $/Mtok$0.2887$0.30
Output $/Mtok$0.9594$2.50
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computable$0.466
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3 better than Gemini 2.5 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3 for output tokens 2.6x cheaper ($0.9594 vs $2.50 per million) and work measured by Kagi LLM Benchmark or Design Arena: SVG, where it leads.

Which is cheaper, DeepSeek V3 or Gemini 2.5 Flash?

DeepSeek V3 costs $0.2887 per million input tokens and $0.9594 per million output tokens; Gemini 2.5 Flash costs $0.30 and $2.50. Cost per solved task is known for Gemini 2.5 Flash only.

Which has the bigger context window, DeepSeek V3 or Gemini 2.5 Flash?

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

How many benchmarks is the DeepSeek V3 vs Gemini 2.5 Flash comparison based on?

10 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3's coding index rests on 0 independent benchmarks and Gemini 2.5 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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