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DeepSeek V4 Pro 0813 vs Gemini 2.5 Flash

DeepSeek V4 Pro 0813 leads Gemini 2.5 Flash on the Artificial Analysis Intelligence Index, 36.0 to 15.5, and DeepSeek V4 Pro 0813 costs 1.3x less per output token ($1.98 vs $2.50 per million). Updated October 21, 2026; 36 benchmarks have a result for both.

DeepSeek V4 Pro 0813DeepSeek
Coding
56.1
Overall
60.8
Output $/M
$1.98
35
Gemini 2.5 FlashGoogle
Coding
No data
Overall
34.3
Output $/M
$2.50
1
vs boards won of 36 shared

DeepSeek V4 Pro 0813 or Gemini 2.5 Flash: which to pick

Only DeepSeek V4 Pro 0813 has a coding score, 56.1 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding.

Pick Gemini 2.5 Flash for work measured by MedScribe (Vals AI), where it leads.

Shared results
36
DeepSeek V4 Pro 0813 only
42
Gemini 2.5 Flash only
37
Like-for-like categories
6 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 V4 Pro 0813 56.1 from 5 benchmarks, Gemini 2.5 Flash not benchmarked.
Widest category
Reasoning, 25.3 points apart on average over 7 shared benchmarks.
Widest single gap
ARC-AGI-2: DeepSeek V4 Pro 0813 61.3% against Gemini 2.5 Flash 2.5%, 58.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0813 $1.98 against Gemini 2.5 Flash $2.50 per million output tokens, 1.3x apart.
Context window
Both take 1.05M tokens.

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 V4 Pro 0813BarsGemini 2.5 FlashTies
Coding20
Intelligence20
Reasoning70
Math20
Knowledge50
General171
All shared boards351
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
Coding benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 FlashLeader
SWE-bench VerifiedNot measured28.7%Only Gemini 2.5 Flash measured
LMArena WebDev1582Not measuredOnly DeepSeek V4 Pro 0813 measured
AA Coding Index68.8Not measuredOnly DeepSeek V4 Pro 0813 measured
LiveCodeBench (Vals AI)87.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
SWE-bench Verified (Vals AI)96.4%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench 4 (Vals AI)14.1%Not measuredOnly DeepSeek V4 Pro 0813 measured
Vibe Code Bench (Vals AI)82.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
Code migration (Vals AI)41.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
ProgramBench (Vals AI)0.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
IOI (Vals AI)51.6%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench 2.1 (Vals AI)54.7%Not measuredOnly DeepSeek V4 Pro 0813 measured
Vibe Code Bench 1-100 (Vals AI)17.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
SkillsBench (Vals AI)53.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
CyberBench (Vals AI)72.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
LiveCodeBench (Artificial Analysis run)Not measured69.5%Only Gemini 2.5 Flash measured
SciCode51.0%Not measuredOnly DeepSeek V4 Pro 0813 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
FrontierCode28.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
WeirdML66.2%Not measuredOnly DeepSeek V4 Pro 0813 measured
ALE-Bench1403.2Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: coding14691423DeepSeek V4 Pro 0813
LMArena Text: software and IT14621425DeepSeek V4 Pro 0813
LMArena WebDev: React1588Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena WebDev: HTML1566Not measuredOnly DeepSeek V4 Pro 0813 measured
Neither model has a result on the other 14 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 FlashLeader
AA Intelligence Index36.015.5DeepSeek V4 Pro 0813
Epoch Capabilities Index155.6142.9DeepSeek V4 Pro 0813
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index14 boards, none shared
Agentic work benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 FlashLeader
AA Agentic Index41.3Not measuredOnly DeepSeek V4 Pro 0813 measured
SREBench (Vals AI)1.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
Finance Agent (Vals AI)50.4%Not measuredOnly DeepSeek V4 Pro 0813 measured
Tax Agent Bench (Vals AI)26.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
Legal Research Bench (Vals AI)40.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
Harvey's Legal Agent Benchmark (Vals AI)10.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
Excel Modeling Benchmark (Vals AI)52.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
τ²-Bench TelecomNot measured31.6%Only Gemini 2.5 Flash measured
APEX-Agents47.3%Not measuredOnly DeepSeek V4 Pro 0813 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 27 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 FlashLeader
GPQA Diamond92.4%Not measuredOnly DeepSeek V4 Pro 0813 measured
GPQA Diamond (Artificial Analysis run)92.8%79.0%DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)41.0%12.1%DeepSeek V4 Pro 0813
GPQA Diamond (Epoch AI run)91.7%Not measuredOnly DeepSeek V4 Pro 0813 measured
ARC-AGI90.5%33.3%DeepSeek V4 Pro 0813
ARC-AGI-261.3%2.5%DeepSeek V4 Pro 0813
SimpleBenchNot measured41.2%Only Gemini 2.5 Flash measured
Chess puzzles46.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
Mystery game puzzles43.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: hard prompts14581422DeepSeek V4 Pro 0813
LMArena Text: expert14591426DeepSeek V4 Pro 0813
LMArena Text: hard prompts in English14631420DeepSeek V4 Pro 0813
LMArena Vision: diagramsNot measured1245Only Gemini 2.5 Flash measured
LMArena Vision: homeworkNot measured1244Only Gemini 2.5 Flash measured
Kagi LLM BenchmarkNot measured56.8%Only Gemini 2.5 Flash measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 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 AIME98.6%Not measuredOnly DeepSeek V4 Pro 0813 measured
FrontierMath, tiers 1 to 364.6%Not measuredOnly DeepSeek V4 Pro 0813 measured
FrontierMath, tier 426.8%Not measuredOnly DeepSeek V4 Pro 0813 measured
ProofBench50.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: math14411411DeepSeek V4 Pro 0813
LMArena Text: mathematical work14431422DeepSeek V4 Pro 0813
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
Knowledge benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 FlashLeader
MMLU Pro87.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
LegalBench (Vals AI)82.4%Not measuredOnly DeepSeek V4 Pro 0813 measured
CorpFin (Vals AI)65.4%Not measuredOnly DeepSeek V4 Pro 0813 measured
TaxEval (Vals AI)73.1%Not measuredOnly DeepSeek V4 Pro 0813 measured
MedCode (Vals AI)42.5%40.4%DeepSeek V4 Pro 0813
MMLU Pro (Artificial Analysis run)Not measured83.2%Only Gemini 2.5 Flash measured
SimpleQA Verified52.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: science14571433DeepSeek V4 Pro 0813
LMArena Text: medicine and healthcare14461428DeepSeek V4 Pro 0813
LMArena Text: legal and government14591430DeepSeek V4 Pro 0813
LMArena Text: business and finance14421404DeepSeek V4 Pro 0813
FACTS Benchmark SuiteNot measured47.2%Only Gemini 2.5 Flash measured
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 FlashLeader
Design Arena: websitesNot measured1074Only Gemini 2.5 Flash measured
Design Arena: UI componentsNot measured1005Only Gemini 2.5 Flash measured
Design Arena: game devNot measured1005Only Gemini 2.5 Flash measured
Design Arena: data vizNot measured1060Only Gemini 2.5 Flash measured
Design Arena: 3DNot measured1021Only Gemini 2.5 Flash measured
Design Arena: all code categoriesNot measured1059Only Gemini 2.5 Flash measured
Design Arena: SVGNot measured1020Only Gemini 2.5 Flash measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index171
General benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 FlashLeader
Vals Index53.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
SAGE (Vals AI)Not measured44.8%Only Gemini 2.5 Flash measured
MedScribe (Vals AI)80.2%83.0%Gemini 2.5 Flash
IFBenchNot measured50.3%Only Gemini 2.5 Flash measured
Long context reasoning (AA-LCR)80.3%65.3%DeepSeek V4 Pro 0813
DTBench93.9%76.5%DeepSeek V4 Pro 0813
LMCA45.5%27.5%DeepSeek V4 Pro 0813
LMArena Text14461417DeepSeek V4 Pro 0813
LMArena Text: instruction following14481405DeepSeek V4 Pro 0813
LMArena Text: creative writing14391400DeepSeek V4 Pro 0813
LMArena VisionNot measured1235Only Gemini 2.5 Flash measured
LMArena Text: English14571418DeepSeek V4 Pro 0813
LMArena Text: non-English14311409DeepSeek V4 Pro 0813
LMArena Text: Chinese14811449DeepSeek V4 Pro 0813
LMArena Text: GermanNot measured1417Only Gemini 2.5 Flash measured
LMArena Text: JapaneseNot measured1396Only Gemini 2.5 Flash measured
LMArena Text: Korean14491385DeepSeek V4 Pro 0813
LMArena Text: French14461432DeepSeek V4 Pro 0813
LMArena Text: Spanish14351422DeepSeek V4 Pro 0813
LMArena Text: Russian14481415DeepSeek V4 Pro 0813
LMArena Text: PolishNot measured1413Only Gemini 2.5 Flash measured
LMArena Text: multi-turn14541408DeepSeek V4 Pro 0813
LMArena Text: longer queries14581419DeepSeek V4 Pro 0813
LMArena Text: writing and language14431405DeepSeek V4 Pro 0813
LMArena Text: entertainment and media14241393DeepSeek V4 Pro 0813
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 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Flash
BenchmarkDeepSeek V4 Pro 0813Gemini 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 V4 Pro 0813$0.0016Fits in one request
Gemini 2.5 Flash$0.0015Fits in one request

Gemini 2.5 Flash costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0813$0.039Fits in one request
Gemini 2.5 Flash$0.022Fits in one request

Gemini 2.5 Flash costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0813$0.152Fits in one request
Gemini 2.5 Flash$0.085Fits in one request

Gemini 2.5 Flash 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 V4 Pro 0813 and Gemini 2.5 Flash
SpecificationDeepSeek V4 Pro 0813Google Gemini 2.5 Flash
MakerDeepSeekGoogle
WeightsOpen weightsNo public weights listed
ReleasedAugust 12, 2026June 17, 2025
Context window1.05M1.05M
Input $/Mtok$0.66$0.30
Output $/Mtok$1.98$2.50
Coding index56.1Not benchmarked
Independent measurements behind it50
Cost per solved task$0.10$0.466
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0813 better than Gemini 2.5 Flash for coding?

Only DeepSeek V4 Pro 0813 has a coding score, 56.1 on the Vibe Coding Index; Gemini 2.5 Flash has none, so the two cannot be ranked on coding. Pick Gemini 2.5 Flash for work measured by MedScribe (Vals AI), where it leads.

Which is cheaper, DeepSeek V4 Pro 0813 or Gemini 2.5 Flash?

DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; Gemini 2.5 Flash costs $0.30 and $2.50. Per solved SWE-bench Verified task, DeepSeek V4 Pro 0813 costs $0.10 and Gemini 2.5 Flash $0.466.

Which has the bigger context window, DeepSeek V4 Pro 0813 or Gemini 2.5 Flash?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4 Pro 0813 vs Gemini 2.5 Flash comparison based on?

36 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 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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