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DeepSeek V4 Pro 0813 vs Kimi K2 0711

Updated October 21, 2026. 12 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

DeepSeek V4 Pro 0813DeepSeek
Coding
54.6
Overall
36.0
Output $/M
$1.98
12
Kimi K2 0711Moonshot AI
Coding
64.7
Overall
12.7
Output $/M
$2.30
0
vs boards won of 12 shared

Decision reading

Pick Kimi K2 0711 for coding: it scores 64.7 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813.

Pick DeepSeek V4 Pro 0813 when output tokens cost 1.2x less, or when the context window is larger, 1.05M against 131K tokens.

Shared results
12
DeepSeek V4 Pro 0813 only
66
Kimi K2 0711 only
24
Like-for-like categories
5 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 54.6 from 1 benchmark, Kimi K2 0711 64.7 from 2 benchmarks.
Widest category
General, 27.3 points apart on average over 1 shared benchmark.
Widest single gap
Humanity's Last Exam (Artificial Analysis run): DeepSeek V4 Pro 0813 41.0% against Kimi K2 0711 7.4%, 33.6 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Pro 0813 $1.98 against Kimi K2 0711 $2.30 per million output tokens, 1.2x apart.
Context window
DeepSeek V4 Pro 0813 takes 1.05M tokens, Kimi K2 0711 131K.

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 0813BarsKimi K2 0711Ties
Coding20
Intelligence20
Reasoning30
Knowledge40
General10
All shared boards120
CodingLike-for-likeFour of these boards feed the Vibe Coding Index20
Coding benchmarks for DeepSeek V4 Pro 0813 and Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
Aider polyglotNot measured59.1%Only Kimi K2 0711 measured
SWE-bench VerifiedNot measured71.2%Only Kimi K2 0711 measured
LMArena WebDev1582Not measuredOnly DeepSeek V4 Pro 0813 measured
AA Coding Index68.8Not measuredOnly DeepSeek V4 Pro 0813 measured
LiveCodeBench (Vals AI)87.5%70.5%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 measured55.6%Only Kimi K2 0711 measured
SciCode51.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured15.9%Only Kimi K2 0711 measured
Terminal-BenchNot measured27.8%Only Kimi K2 0711 measured
FrontierCode28.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
GSO-BenchNot measured4.9%Only Kimi K2 0711 measured
WeirdML66.2%39.4%DeepSeek V4 Pro 0813
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
Neither model has a result on the other 11 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V4 Pro 0813 and Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
AA Intelligence Index36.012.7DeepSeek V4 Pro 0813
Epoch Capabilities Index155.6140.0DeepSeek V4 Pro 0813
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Agentic work benchmarks for DeepSeek V4 Pro 0813 and Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
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 measured61.1%Only Kimi K2 0711 measured
APEX-Agents47.3%Not measuredOnly DeepSeek V4 Pro 0813 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 Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
GPQA Diamond92.4%71.5%DeepSeek V4 Pro 0813
GPQA Diamond (Artificial Analysis run)92.8%76.6%DeepSeek V4 Pro 0813
Humanity's Last Exam (Artificial Analysis run)41.0%7.4%DeepSeek V4 Pro 0813
GPQA Diamond (Epoch AI run)91.7%Not measuredOnly DeepSeek V4 Pro 0813 measured
ARC-AGI90.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
ARC-AGI-261.3%Not measuredOnly DeepSeek V4 Pro 0813 measured
SimpleBenchNot measured26.3%Only Kimi K2 0711 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 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 index11 boards, none shared
Math benchmarks for DeepSeek V4 Pro 0813 and Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
AIMENot measured62.7%Only Kimi K2 0711 measured
MATH 500 (Vals AI)Not measured94.2%Only Kimi K2 0711 measured
MGSM (Vals AI)Not measured91.0%Only Kimi K2 0711 measured
AA Math IndexNot measured57.0Only Kimi K2 0711 measured
AIME 2025 (Artificial Analysis run)Not measured57.0%Only Kimi K2 0711 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: 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 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for DeepSeek V4 Pro 0813 and Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
MMLU Pro87.0%79.4%DeepSeek V4 Pro 0813
LegalBench (Vals AI)82.4%81.5%DeepSeek V4 Pro 0813
CorpFin (Vals AI)65.4%50.4%DeepSeek V4 Pro 0813
TaxEval (Vals AI)73.1%70.2%DeepSeek V4 Pro 0813
MedQA (Vals AI)Not measured84.0%Only Kimi K2 0711 measured
MedCode (Vals AI)42.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
MMLU Pro (Artificial Analysis run)Not measured82.4%Only Kimi K2 0711 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 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for DeepSeek V4 Pro 0813 and Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
Design Arena: websitesNot measured1050Only Kimi K2 0711 measured
Design Arena: UI componentsNot measured1030Only Kimi K2 0711 measured
Design Arena: game devNot measured974Only Kimi K2 0711 measured
Design Arena: data vizNot measured1018Only Kimi K2 0711 measured
Design Arena: all code categoriesNot measured1034Only Kimi K2 0711 measured
Neither model has a result on the other 4 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for DeepSeek V4 Pro 0813 and Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
Vals Index53.0%Not measuredOnly DeepSeek V4 Pro 0813 measured
MedScribe (Vals AI)80.2%Not measuredOnly DeepSeek V4 Pro 0813 measured
IFBenchNot measured41.5%Only Kimi K2 0711 measured
Long context reasoning (AA-LCR)80.3%53.0%DeepSeek V4 Pro 0813
DTBench93.9%Not measuredOnly DeepSeek V4 Pro 0813 measured
LMCA45.5%Not measuredOnly DeepSeek V4 Pro 0813 measured
Fiction.LiveBenchNot measured61.1%Only Kimi K2 0711 measured
Creative writing (Lech Mazur)Not measured85.6%Only Kimi K2 0711 measured
CL-benchNot measured11.9%Only Kimi K2 0711 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 23 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 Kimi K2 0711
BenchmarkDeepSeek V4 Pro 0813Kimi K2 0711Leader
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
Kimi K2 0711$0.0017Fits 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
Kimi K2 0711$0.035Fits in one request

Kimi K2 0711 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Pro 0813$0.152Fits in one request
Kimi K2 0711$0.137Exceeds the context window

Kimi K2 0711 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 Kimi K2 0711
SpecificationDeepSeek V4 Pro 0813MoonshotAI Kimi K2 0711
MakerDeepSeekMoonshot AI
WeightsOpen weightsOpen weights
ReleasedAugust 12, 2026July 11, 2025
Context window1.05M131K
Input $/Mtok$0.66$0.57
Output $/Mtok$1.98$2.30
Coding index54.664.7
Independent measurements behind it12
Cost per solved task$0.10Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Pro 0813 better than Kimi K2 0711 for coding?

Pick Kimi K2 0711 for coding: it scores 64.7 on the Vibe Coding Index against 54.6 for DeepSeek V4 Pro 0813. Pick DeepSeek V4 Pro 0813 when output tokens cost 1.2x less, or when the context window is larger, 1.05M against 131K tokens.

Which is cheaper, DeepSeek V4 Pro 0813 or Kimi K2 0711?

DeepSeek V4 Pro 0813 costs $0.66 per million input tokens and $1.98 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for DeepSeek V4 Pro 0813 only.

Which has the bigger context window, DeepSeek V4 Pro 0813 or Kimi K2 0711?

DeepSeek V4 Pro 0813, with 1.05M tokens against 131K.

How many benchmarks is the DeepSeek V4 Pro 0813 vs Kimi K2 0711 comparison based on?

12 benchmarks have a result for both models as of October 21, 2026. DeepSeek V4 Pro 0813's coding index rests on 1 independent benchmark and Kimi K2 0711's on 2. Where only one model has a result, the page says so instead of naming a winner.

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