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DeepSeek V4 Pro 0813 vs Gemini 2.5 Pro Preview 06-05

DeepSeek V4 Pro 0813 costs 5.1x less per output token than Gemini 2.5 Pro Preview 06-05 ($1.98 vs $10.00 per million). Updated October 22, 2026; 4 benchmarks have a result for both.

DeepSeek V4 Pro 0813DeepSeek
Coding
56.1
Overall
60.8
Output $/M
$1.98
4
Gemini 2.5 Pro Preview 06-05Google
Coding
No data
Overall
No data
Output $/M
$10.00
0
vs boards won of 4 shared

DeepSeek V4 Pro 0813 or Gemini 2.5 Pro Preview 06-05: which to pick

Only DeepSeek V4 Pro 0813 has a coding score, 56.1 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
4
DeepSeek V4 Pro 0813 only
74
Gemini 2.5 Pro Preview 06-05 only
11
Like-for-like categories
2 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 Pro Preview 06-05 not benchmarked.
Widest category
Reasoning, 12.4 points apart on average over 3 shared benchmarks.
Widest single gap
Humanity's Last Exam (Artificial Analysis run): DeepSeek V4 Pro 0813 41.0% against Gemini 2.5 Pro Preview 06-05 19.9%, 21.1 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0813 $1.98 against Gemini 2.5 Pro Preview 06-05 $10.00 per million output tokens, 5.1x 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 Pro Preview 06-05Ties
Coding10
Reasoning30
All shared boards40
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
Aider polyglotNot measured83.1%Only Gemini 2.5 Pro Preview 06-05 measured
LMArena WebDev1582Not measuredOnly DeepSeek V4 Pro 0813 measured
AA Coding Index68.8Not measuredOnly DeepSeek V4 Pro 0813 measured
LiveCodeBench (Vals AI)87.5%79.2%DeepSeek V4 Pro 0813
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 measured77.8%Only Gemini 2.5 Pro Preview 06-05 measured
SciCode51.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
FrontierCode28.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
GSO-BenchNot measured3.9%Only Gemini 2.5 Pro Preview 06-05 measured
WeirdML66.2%Not measuredOnly DeepSeek V4 Pro 0813 measured
ALE-Bench1403.2Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: coding1469Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: software and IT1462Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena WebDev: React1588Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena WebDev: HTML1566Not measuredOnly DeepSeek V4 Pro 0813 measured
SciCodeNot measured7.7%Only Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 14 boards here
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
Intelligence benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
AA Intelligence Index36.0Not measuredOnly DeepSeek V4 Pro 0813 measured
Epoch Capabilities Index155.6Not measuredOnly DeepSeek V4 Pro 0813 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index12 boards, none shared
Agentic work benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
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
APEX-Agents47.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
METR time horizonsNot measured55.4%Only Gemini 2.5 Pro Preview 06-05 measured
Remote Labor IndexNot measured0.8%Only Gemini 2.5 Pro Preview 06-05 measured
DeepResearch BenchNot measured42.8%Only Gemini 2.5 Pro Preview 06-05 measured
Neither model has a result on the other 29 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
GPQA Diamond92.4%Not measuredOnly DeepSeek V4 Pro 0813 measured
GPQA Diamond (Artificial Analysis run)92.8%83.6%DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)41.0%19.9%DeepSeek V4 Pro 0813
GPQA Diamond (Epoch AI run)91.7%84.8%DeepSeek V4 Pro 0813
ARC-AGI90.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
ARC-AGI-261.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
SimpleBenchNot measured62.4%Only Gemini 2.5 Pro Preview 06-05 measured
Chess puzzles46.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
Mystery game puzzles43.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
VPCTNot measured46.4%Only Gemini 2.5 Pro Preview 06-05 measured
LMArena Text: hard prompts1458Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: expert1459Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: hard prompts in English1463Not measuredOnly DeepSeek V4 Pro 0813 measured
Neither model has a result on the other 9 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Math benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
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: math1441Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: mathematical work1443Not measuredOnly DeepSeek V4 Pro 0813 measured
Neither model has a result on the other 7 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
Knowledge benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
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%Not measuredOnly DeepSeek V4 Pro 0813 measured
MMLU Pro (Artificial Analysis run)Not measured85.8%Only Gemini 2.5 Pro Preview 06-05 measured
SimpleQA Verified52.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: science1457Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: medicine and healthcare1446Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: legal and government1459Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: business and finance1442Not measuredOnly DeepSeek V4 Pro 0813 measured
Neither model has a result on the other 7 boards here
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Web design benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
Neither model has a result on 9 boards here
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
General benchmarks for DeepSeek V4 Pro 0813 and Gemini 2.5 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
Vals Index53.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
MedScribe (Vals AI)80.2%Not measuredOnly DeepSeek V4 Pro 0813 measured
Long context reasoning (AA-LCR)80.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
DTBench93.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMCA45.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
Fiction.LiveBenchNot measured91.7%Only Gemini 2.5 Pro Preview 06-05 measured
LMArena Text1446Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: instruction following1448Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: creative writing1439Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: English1457Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: non-English1431Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: Chinese1481Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: Korean1449Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: French1446Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: Spanish1435Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: Russian1448Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: multi-turn1454Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: longer queries1458Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: writing and language1443Not measuredOnly DeepSeek V4 Pro 0813 measured
LMArena Text: entertainment and media1424Not measuredOnly DeepSeek V4 Pro 0813 measured
Neither model has a result on the other 26 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 Pro Preview 06-05
BenchmarkDeepSeek V4 Pro 0813Gemini 2.5 Pro Preview 06-05Leader
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 Pro Preview 06-05$0.0063Fits in one request

DeepSeek V4 Pro 0813 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Pro 0813$0.039Fits in one request
Gemini 2.5 Pro Preview 06-05$0.092Fits in one request

DeepSeek V4 Pro 0813 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0813$0.152Fits in one request
Gemini 2.5 Pro Preview 06-05$0.350Fits in one request

DeepSeek V4 Pro 0813 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 Pro Preview 06-05
SpecificationDeepSeek V4 Pro 0813Google Gemini 2.5 Pro Preview 06-05
MakerDeepSeekGoogle
WeightsOpen weightsNo public weights listed
ReleasedAugust 12, 2026June 5, 2025
Context window1.05M1.05M
Input $/Mtok$0.66$1.25
Output $/Mtok$1.98$10.00
Coding index56.1Not benchmarked
Independent measurements behind it50
Cost per solved task$0.10Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0813 better than Gemini 2.5 Pro Preview 06-05 for coding?

Only DeepSeek V4 Pro 0813 has a coding score, 56.1 on the Vibe Coding Index; Gemini 2.5 Pro Preview 06-05 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, DeepSeek V4 Pro 0813 or Gemini 2.5 Pro Preview 06-05?

DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; Gemini 2.5 Pro Preview 06-05 costs $1.25 and $10.00. Cost per solved task is known for DeepSeek V4 Pro 0813 only.

Which has the bigger context window, DeepSeek V4 Pro 0813 or Gemini 2.5 Pro Preview 06-05?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4 Pro 0813 vs Gemini 2.5 Pro Preview 06-05 comparison based on?

4 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Pro 0813's coding index rests on 5 independent benchmarks and Gemini 2.5 Pro Preview 06-05's on 0. Where only one model has a result, the page says so instead of naming a winner.

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