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DeepSeek V3.2 Exp vs Kimi K2 0711

DeepSeek V3.2 Exp leads Kimi K2 0711 on the Artificial Analysis Intelligence Index, 16.6 to 12.7, and DeepSeek V3.2 Exp costs 5.6x less per output token ($0.41 vs $2.30 per million). Updated October 22, 2026; 22 benchmarks have a result for both.

Replace DeepSeek V3.2 Exp Replace Kimi K2 0711
DeepSeek V3.2 ExpDeepSeek
Coding
No data
Overall
No data
Output $/M
$0.41
20
Kimi K2 0711Moonshot AI
Coding
No data
Overall
No data
Output $/M
$2.30
2
vs boards won of 22 shared

DeepSeek V3.2 Exp or Kimi K2 0711: which to pick

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

Pick DeepSeek V3.2 Exp for output tokens 5.6x cheaper ($0.41 vs $2.30 per million) and a larger context window (164K against 131K tokens).

Model ADeepSeek V3.2 ExpDeepSeekNot benchmarked1 independent benchmarkNo cost per solved taskModel BKimi K2 0711Moonshot AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
22
DeepSeek V3.2 Exp only
37
Kimi K2 0711 only
15
Like-for-like categories
8 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 V3.2 Exp not benchmarked, Kimi K2 0711 not benchmarked.
Widest category
Math, 30.7 points apart on average over 2 shared benchmarks.
Widest single gap
AA Math Index: DeepSeek V3.2 Exp 87.7 against Kimi K2 0711 57.0, 30.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V3.2 Exp $0.41 against Kimi K2 0711 $2.30 per million output tokens, 5.6x apart.
Context window
DeepSeek V3.2 Exp takes 164K 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 V3.2 ExpBarsKimi K2 0711Ties
Coding40
Intelligence20
Agentic work01
Reasoning21
Math20
Knowledge10
Web design50
General40
All shared boards202
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi K2 0711Leader
Aider polyglot74.2%59.1%DeepSeek V3.2 Exp
SWE-bench VerifiedNot measured71.2%Only Kimi K2 0711 measured
LMArena WebDev1272Not measuredOnly DeepSeek V3.2 Exp measured
LiveCodeBench (Vals AI)Not measured70.5%Only Kimi K2 0711 measured
LiveCodeBench (Artificial Analysis run)78.9%55.6%DeepSeek V3.2 Exp
Terminal-Bench Hard (Artificial Analysis run)31.1%15.9%DeepSeek V3.2 Exp
Terminal-BenchNot measured27.8%Only Kimi K2 0711 measured
GSO-BenchNot measured4.9%Only Kimi K2 0711 measured
WeirdML39.5%39.4%DeepSeek V3.2 Exp
LMArena Text: coding1438Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: software and IT1438Not measuredOnly DeepSeek V3.2 Exp measured
LMArena WebDev: HTML1281Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi K2 0711Leader
AA Intelligence Index16.612.7DeepSeek V3.2 Exp
Epoch Capabilities Index144.9140.0DeepSeek V3.2 Exp
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi K2 0711Leader
τ²-Bench Telecom33.9%61.1%Kimi K2 0711
TheAgentCompany42.9%Not measuredOnly DeepSeek V3.2 Exp measured
Berkeley Function Calling Leaderboard (BFCL)56.7%Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index21
Reasoning benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi K2 0711Leader
GPQA DiamondNot measured71.5%Only Kimi K2 0711 measured
GPQA Diamond (Artificial Analysis run)79.7%76.6%DeepSeek V3.2 Exp
Humanity's Last Exam (Artificial Analysis run)14.9%7.4%DeepSeek V3.2 Exp
SimpleBenchNot measured26.3%Only Kimi K2 0711 measured
LMArena Text: hard prompts1429Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: expert1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: hard prompts in English1444Not measuredOnly DeepSeek V3.2 Exp measured
Kagi LLM Benchmark52.2%64.4%Kimi K2 0711
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi 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 Index87.757.0DeepSeek V3.2 Exp
AIME 2025 (Artificial Analysis run)87.7%57.0%DeepSeek V3.2 Exp
LMArena Text: math1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: mathematical work1433Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi K2 0711Leader
MMLU ProNot measured79.4%Only Kimi K2 0711 measured
LegalBench (Vals AI)Not measured81.5%Only Kimi K2 0711 measured
CorpFin (Vals AI)Not measured50.4%Only Kimi K2 0711 measured
TaxEval (Vals AI)Not measured70.2%Only Kimi K2 0711 measured
MedQA (Vals AI)Not measured84.0%Only Kimi K2 0711 measured
MMLU Pro (Artificial Analysis run)85.0%82.4%DeepSeek V3.2 Exp
LMArena Text: science1443Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: medicine and healthcare1468Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: legal and government1419Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: business and finance1412Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index50
Web design benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi K2 0711Leader
Design Arena: websites11781050DeepSeek V3.2 Exp
Design Arena: UI components11641027DeepSeek V3.2 Exp
Design Arena: game dev1144973DeepSeek V3.2 Exp
Design Arena: data viz11521018DeepSeek V3.2 Exp
Design Arena: 3D1148Not measuredOnly DeepSeek V3.2 Exp measured
Design Arena: all code categories11701033DeepSeek V3.2 Exp
Design Arena: SVG1031Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index40
General benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi K2 0711Leader
IFBench54.1%41.5%DeepSeek V3.2 Exp
Long context reasoning (AA-LCR)72.3%53.0%DeepSeek V3.2 Exp
DTBench87.7%Not measuredOnly DeepSeek V3.2 Exp measured
LMCA29.1%Not measuredOnly DeepSeek V3.2 Exp measured
Fiction.LiveBench83.3%61.1%DeepSeek V3.2 Exp
Creative writing (Lech Mazur)Not measured85.6%Only Kimi K2 0711 measured
CL-bench13.2%11.9%DeepSeek V3.2 Exp
CL-bench Life9.5%Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text1425Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: instruction following1401Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: creative writing1404Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: English1441Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: non-English1404Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Chinese1461Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: German1440Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Japanese1331Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Korean1372Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: French1434Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Spanish1441Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Russian1412Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: Polish1435Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: multi-turn1422Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: longer queries1418Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: writing and language1407Not measuredOnly DeepSeek V3.2 Exp measured
LMArena Text: entertainment and media1407Not measuredOnly DeepSeek V3.2 Exp measured
Neither model has a result on the other 21 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V3.2 Exp and Kimi K2 0711
BenchmarkDeepSeek V3.2 ExpKimi 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 V3.2 Exp$0.0005Fits in one request
Kimi K2 0711$0.0017Fits in one request

DeepSeek V3.2 Exp costs less

Repository review

50K input + 3K output tokens

DeepSeek V3.2 Exp$0.015Fits in one request
Kimi K2 0711$0.035Fits in one request

DeepSeek V3.2 Exp costs less

Agent loop

200K input + 10K output tokens

DeepSeek V3.2 Exp$0.058Exceeds the context window
Kimi K2 0711$0.137Exceeds the context window

DeepSeek V3.2 Exp 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 V3.2 Exp and Kimi K2 0711
SpecificationDeepSeek V3.2 ExpMoonshotAI Kimi K2 0711
MakerDeepSeekMoonshot AI
WeightsOpen weightsOpen weights
ReleasedSeptember 29, 2025July 11, 2025
Context window164K131K
Input $/Mtok$0.27$0.57
Output $/Mtok$0.41$2.30
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V3.2 Exp better than Kimi K2 0711 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick DeepSeek V3.2 Exp for output tokens 5.6x cheaper ($0.41 vs $2.30 per million) and a larger context window (164K against 131K tokens).

Which is cheaper, DeepSeek V3.2 Exp or Kimi K2 0711?

DeepSeek V3.2 Exp costs $0.27 per million input tokens and $0.41 per million output tokens; Kimi K2 0711 costs $0.57 and $2.30. Cost per solved task is known for neither of them.

Which has the bigger context window, DeepSeek V3.2 Exp or Kimi K2 0711?

DeepSeek V3.2 Exp, with 164K tokens against 131K.

How many benchmarks is the DeepSeek V3.2 Exp vs Kimi K2 0711 comparison based on?

22 benchmarks have a result for both models as of October 22, 2026. DeepSeek V3.2 Exp's coding index rests on 1 independent benchmark and Kimi K2 0711's on 0. Where only one model has a result, the page says so instead of naming a winner.

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