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Kimi K2 0711 vs Qwen3 VL 235B A22B Instruct

Kimi K2 0711 leads Qwen3 VL 235B A22B Instruct on the Artificial Analysis Intelligence Index, 12.7 to 9.9, and Qwen3 VL 235B A22B Instruct costs 1.2x less per output token ($1.90 vs $2.30 per million). Updated October 22, 2026; 11 benchmarks have a result for both.

Kimi K2 0711Moonshot AI
Coding
No data
Overall
No data
Output $/M
$2.30
3
Qwen3 VL 235B A22B InstructQwen
Coding
No data
Overall
No data
Output $/M
$1.90
8
vs boards won of 11 shared

Kimi K2 0711 or Qwen3 VL 235B A22B Instruct: which to pick

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

Pick Kimi K2 0711 for work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.

Shared results
11
Kimi K2 0711 only
26
Qwen3 VL 235B A22B Instruct only
38
Like-for-like categories
7 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
Kimi K2 0711 not benchmarked, Qwen3 VL 235B A22B Instruct not benchmarked.
Widest category
Math, 31.3 points apart on average over 2 shared benchmarks.
Widest single gap
AIME 2025 (Artificial Analysis run): Kimi K2 0711 57.0% against Qwen3 VL 235B A22B Instruct 88.3%, 31.3 points apart on a 0 to 100 scale.
Output price
Kimi K2 0711 $2.30 against Qwen3 VL 235B A22B Instruct $1.90 per million output tokens, 1.2x apart.
Context window
Kimi K2 0711 takes 131K tokens, Qwen3 VL 235B A22B Instruct 262K.

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
CategoryKimi K2 0711BarsQwen3 VL 235B A22B InstructTies
Coding11
Intelligence10
Agentic work10
Reasoning02
Math02
Knowledge01
General02
All shared boards38
CodingLike-for-likeSix of these boards feed the Vibe Coding Index11
Coding benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
Aider polyglot59.1%Not measuredOnly Kimi K2 0711 measured
SWE-bench Verified71.2%Not measuredOnly Kimi K2 0711 measured
LiveCodeBench (Vals AI)70.5%Not measuredOnly Kimi K2 0711 measured
LiveCodeBench (Artificial Analysis run)55.6%64.6%Qwen3 VL 235B A22B Instruct
Terminal-Bench Hard (Artificial Analysis run)15.9%11.4%Kimi K2 0711
Terminal-Bench27.8%Not measuredOnly Kimi K2 0711 measured
GSO-Bench4.9%Not measuredOnly Kimi K2 0711 measured
WeirdML39.4%Not measuredOnly Kimi K2 0711 measured
LMArena Text: codingNot measured1438Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: software and ITNot measured1442Only Qwen3 VL 235B A22B Instruct measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
AA Intelligence Index12.79.9Kimi K2 0711
Epoch Capabilities Index140.0Not measuredOnly Kimi K2 0711 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
τ²-Bench Telecom61.1%54.1%Kimi K2 0711
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
Reasoning benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
GPQA Diamond71.5%Not measuredOnly Kimi K2 0711 measured
GPQA Diamond (Artificial Analysis run)76.6%77.2%Qwen3 VL 235B A22B Instruct
Humanity's Last Exam (Artificial Analysis run)7.4%11.9%Qwen3 VL 235B A22B Instruct
SimpleBench26.3%Not measuredOnly Kimi K2 0711 measured
LMArena Text: hard promptsNot measured1428Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: expertNot measured1442Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: hard prompts in EnglishNot measured1439Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: diagramsNot measured1255Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: homeworkNot measured1277Only Qwen3 VL 235B A22B Instruct measured
Kagi LLM Benchmark64.4%Not measuredOnly Kimi K2 0711 measured
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
AIME62.7%Not measuredOnly Kimi K2 0711 measured
MATH 500 (Vals AI)94.2%Not measuredOnly Kimi K2 0711 measured
MGSM (Vals AI)91.0%Not measuredOnly Kimi K2 0711 measured
AA Math Index57.088.3Qwen3 VL 235B A22B Instruct
AIME 2025 (Artificial Analysis run)57.0%88.3%Qwen3 VL 235B A22B Instruct
LMArena Text: mathNot measured1425Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: mathematical workNot measured1419Only Qwen3 VL 235B A22B Instruct measured
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
Knowledge benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
MMLU Pro79.4%Not measuredOnly Kimi K2 0711 measured
LegalBench (Vals AI)81.5%Not measuredOnly Kimi K2 0711 measured
CorpFin (Vals AI)50.4%Not measuredOnly Kimi K2 0711 measured
TaxEval (Vals AI)70.2%Not measuredOnly Kimi K2 0711 measured
MedQA (Vals AI)84.0%Not measuredOnly Kimi K2 0711 measured
MMLU Pro (Artificial Analysis run)82.4%83.6%Qwen3 VL 235B A22B Instruct
LMArena Text: scienceNot measured1444Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: medicine and healthcareNot measured1431Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: legal and governmentNot measured1438Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: business and financeNot measured1433Only Qwen3 VL 235B A22B Instruct measured
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Web design benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
Design Arena: websites1050Not measuredOnly Kimi K2 0711 measured
Design Arena: UI components1027Not measuredOnly Kimi K2 0711 measured
Design Arena: game dev973Not measuredOnly Kimi K2 0711 measured
Design Arena: data viz1018Not measuredOnly Kimi K2 0711 measured
Design Arena: all code categories1033Not measuredOnly 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 index02
General benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
IFBench41.5%56.5%Qwen3 VL 235B A22B Instruct
Long context reasoning (AA-LCR)53.0%63.7%Qwen3 VL 235B A22B Instruct
Fiction.LiveBench61.1%Not measuredOnly Kimi K2 0711 measured
Creative writing (Lech Mazur)85.6%Not measuredOnly Kimi K2 0711 measured
CL-bench11.9%Not measuredOnly Kimi K2 0711 measured
LMArena TextNot measured1420Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: instruction followingNot measured1406Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: creative writingNot measured1366Only Qwen3 VL 235B A22B Instruct measured
LMArena VisionNot measured1247Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: EnglishNot measured1429Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: non-EnglishNot measured1405Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: ChineseNot measured1463Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: GermanNot measured1424Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: JapaneseNot measured1385Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: KoreanNot measured1394Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: FrenchNot measured1452Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: SpanishNot measured1428Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: RussianNot measured1408Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: PolishNot measured1419Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: multi-turnNot measured1428Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: longer queriesNot measured1419Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: writing and languageNot measured1392Only Qwen3 VL 235B A22B Instruct measured
LMArena Text: entertainment and mediaNot measured1368Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: EnglishNot measured1256Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: ChineseNot measured1283Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: reading textNot measured1253Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: humorNot measured1209Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: captioningNot measured1281Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: recognizing thingsNot measured1249Only Qwen3 VL 235B A22B Instruct measured
LMArena Vision: creative writingNot measured1220Only Qwen3 VL 235B A22B Instruct measured
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
BenchmarkKimi K2 0711Qwen3 VL 235B A22B InstructLeader
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

Kimi K2 0711$0.0017Fits in one request
Qwen3 VL 235B A22B Instruct$0.0012Fits in one request

Qwen3 VL 235B A22B Instruct costs less

Repository review

50K input + 3K output tokens

Kimi K2 0711$0.035Fits in one request
Qwen3 VL 235B A22B Instruct$0.016Fits in one request

Qwen3 VL 235B A22B Instruct costs less

Agent loop

200K input + 10K output tokens

Kimi K2 0711$0.137Exceeds the context window
Qwen3 VL 235B A22B Instruct$0.061Fits in one request

Qwen3 VL 235B A22B Instruct 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 Kimi K2 0711 and Qwen3 VL 235B A22B Instruct
SpecificationMoonshotAI Kimi K2 0711Qwen3 VL 235B A22B Instruct
MakerMoonshot AIQwen
WeightsOpen weightsOpen weights
ReleasedJuly 11, 2025September 23, 2025
Context window131K262K
Input $/Mtok$0.57$0.21
Output $/Mtok$2.30$1.90
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Kimi K2 0711 better than Qwen3 VL 235B A22B Instruct for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Kimi K2 0711 for work measured by LiveCodeBench (Artificial Analysis run) or GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, Kimi K2 0711 or Qwen3 VL 235B A22B Instruct?

Kimi K2 0711 costs $0.57 per million input tokens and $2.30 per million output tokens; Qwen3 VL 235B A22B Instruct costs $0.21 and $1.90. Cost per solved task is known for neither of them.

Which has the bigger context window, Kimi K2 0711 or Qwen3 VL 235B A22B Instruct?

Qwen3 VL 235B A22B Instruct, with 262K tokens against 131K.

How many benchmarks is the Kimi K2 0711 vs Qwen3 VL 235B A22B Instruct comparison based on?

11 benchmarks have a result for both models as of October 22, 2026. Kimi K2 0711's coding index rests on 0 independent benchmarks and Qwen3 VL 235B A22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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