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Kimi K2.5 vs Qwen3.5-122B-A10B

Updated October 21, 2026. 47 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Kimi K2.5 Replace Qwen3.5-122B-A10B
Kimi K2.5Moonshot AI
Coding
58.5
Overall
23.5
Output $/M
$2.50
46
Qwen3.5-122B-A10BQwen
Coding
22.9
Overall
17.7
Output $/M
$2.08
1
vs boards won of 47 shared

Decision reading

Pick Kimi K2.5 for coding: it scores 58.5 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B.

Pick Qwen3.5-122B-A10B when output tokens cost 1.2x less, or when the benchmark that matters is IFBench, where it leads.

Model AKimi K2.5Moonshot AI58.5/1002 independent benchmarks$0.24 per solved taskModel BQwen3.5-122B-A10BQwen22.9/1001 independent benchmarkNo cost per solved task
Shared results
47
Kimi K2.5 only
51
Qwen3.5-122B-A10B only
4
Like-for-like categories
7 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
Kimi K2.5 58.5 from 2 benchmarks, Qwen3.5-122B-A10B 22.9 from 1 benchmark.
Widest category
Coding, 8.1 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: React: Kimi K2.5 1429 against Qwen3.5-122B-A10B 1353, 12.8 points apart on a 0 to 100 scale.
Output price
Kimi K2.5 $2.50 against Qwen3.5-122B-A10B $2.08 per million output tokens, 1.2x apart.
Context window
Both take 262K 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
CategoryKimi K2.5BarsQwen3.5-122B-A10BTies
Coding70
Intelligence10
Agentic work10
Reasoning70
Math20
Knowledge40
General241
All shared boards461
CodingLike-for-likeFour of these boards feed the Vibe Coding Index70
Coding benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
SWE-bench Verified70.8%Not measuredOnly Kimi K2.5 measured
SWE-bench Multilingual67.3%Not measuredOnly Kimi K2.5 measured
LMArena WebDev14371361Kimi K2.5
AA Coding Index46.843.3Kimi K2.5
LiveCodeBench (Vals AI)83.9%Not measuredOnly Kimi K2.5 measured
SWE-bench Verified (Vals AI)70.0%Not measuredOnly Kimi K2.5 measured
Vibe Code Bench (Vals AI)17.5%Not measuredOnly Kimi K2.5 measured
Code migration (Vals AI)7.0%Not measuredOnly Kimi K2.5 measured
Terminal-Bench 2.1 (Vals AI)42.0%Not measuredOnly Kimi K2.5 measured
SciCodeNot measured39.7%Only Qwen3.5-122B-A10B measured
Terminal-Bench Hard (Artificial Analysis run)34.8%31.1%Kimi K2.5
Terminal-Bench43.2%Not measuredOnly Kimi K2.5 measured
WeirdML45.6%Not measuredOnly Kimi K2.5 measured
ALE-Bench821.6Not measuredOnly Kimi K2.5 measured
LMArena Text: coding14831436Kimi K2.5
LMArena Text: software and IT14711436Kimi K2.5
LMArena WebDev: React14291353Kimi K2.5
LMArena WebDev: HTML14261351Kimi K2.5
LMArena WebDev: from an image1439Not measuredOnly Kimi K2.5 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
AA Intelligence Index23.517.7Kimi K2.5
Epoch Capabilities Index148.1Not measuredOnly Kimi K2.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
Design Arena: agents building web apps1136Not measuredOnly Kimi K2.5 measured
Design Arena: agents building full-stack apps1114Not measuredOnly Kimi K2.5 measured
Design Arena: agents building mobile apps1147Not measuredOnly Kimi K2.5 measured
Design Arena: agents building Android apps1124Not measuredOnly Kimi K2.5 measured
Design Arena: agents building Godot games1219Not measuredOnly Kimi K2.5 measured
Finance Agent (Vals AI)35.8%Not measuredOnly Kimi K2.5 measured
Legal Research Bench (Vals AI)15.9%Not measuredOnly Kimi K2.5 measured
Excel Modeling Benchmark (Vals AI)28.5%Not measuredOnly Kimi K2.5 measured
τ²-Bench Telecom95.9%93.6%Kimi K2.5
OSWorld63.3%Not measuredOnly Kimi K2.5 measured
Vending-Bench 2$1,198Not measuredOnly Kimi K2.5 measured
Neither model has a result on the other 28 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index70
Reasoning benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
GPQA Diamond84.1%Not measuredOnly Kimi K2.5 measured
MMMU Pro (Vals AI)84.3%Not measuredOnly Kimi K2.5 measured
GPQA Diamond (Artificial Analysis run)87.9%85.7%Kimi K2.5
Humanity's Last Exam (Artificial Analysis run)30.7%25.2%Kimi K2.5
ARC-AGI65.3%Not measuredOnly Kimi K2.5 measured
ARC-AGI-211.8%Not measuredOnly Kimi K2.5 measured
SimpleBench46.8%Not measuredOnly Kimi K2.5 measured
Mystery game puzzlesNot measured17.0%Only Qwen3.5-122B-A10B measured
LMArena Text: hard prompts14531421Kimi K2.5
LMArena Text: expert14661431Kimi K2.5
LMArena Text: hard prompts in English14601431Kimi K2.5
LMArena Vision: diagrams12821249Kimi K2.5
LMArena Vision: homework12971261Kimi K2.5
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
AIME95.6%Not measuredOnly Kimi K2.5 measured
LMArena Text: math14701431Kimi K2.5
LMArena Text: mathematical work14731431Kimi K2.5
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
MMLU Pro85.9%Not measuredOnly Kimi K2.5 measured
CaseLaw (Vals AI)58.7%Not measuredOnly Kimi K2.5 measured
CorpFin (Vals AI)68.3%Not measuredOnly Kimi K2.5 measured
TaxEval (Vals AI)74.2%Not measuredOnly Kimi K2.5 measured
MortgageTax (Vals AI)66.5%Not measuredOnly Kimi K2.5 measured
MedQA (Vals AI)94.4%Not measuredOnly Kimi K2.5 measured
MedCode (Vals AI)39.3%Not measuredOnly Kimi K2.5 measured
SimpleQA Verified34.3%Not measuredOnly Kimi K2.5 measured
LMArena Text: science14591432Kimi K2.5
LMArena Text: medicine and healthcare14481423Kimi K2.5
LMArena Text: legal and government14411422Kimi K2.5
LMArena Text: business and finance14271414Kimi K2.5
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
Design Arena: websites1249Not measuredOnly Kimi K2.5 measured
Design Arena: UI components1236Not measuredOnly Kimi K2.5 measured
Design Arena: game dev1207Not measuredOnly Kimi K2.5 measured
Design Arena: data viz1219Not measuredOnly Kimi K2.5 measured
Design Arena: 3D1205Not measuredOnly Kimi K2.5 measured
Design Arena: all code categories1236Not measuredOnly Kimi K2.5 measured
Design Arena: SVG1149Not measuredOnly Kimi K2.5 measured
Design Arena: ASCII art1165Not measuredOnly Kimi K2.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index241
General benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
SAGE (Vals AI)49.9%Not measuredOnly Kimi K2.5 measured
MedScribe (Vals AI)76.4%Not measuredOnly Kimi K2.5 measured
IFBench70.2%75.7%Qwen3.5-122B-A10B
Long context reasoning (AA-LCR)78.0%76.3%Kimi K2.5
DTBenchNot measured84.3%Only Qwen3.5-122B-A10B measured
LMCANot measured32.2%Only Qwen3.5-122B-A10B measured
Fiction.LiveBench86.1%Not measuredOnly Kimi K2.5 measured
CL-bench19.3%Not measuredOnly Kimi K2.5 measured
CL-bench Life13.2%Not measuredOnly Kimi K2.5 measured
LMArena Text14451417Kimi K2.5
LMArena Text: instruction following14311399Kimi K2.5
LMArena Text: creative writing14221368Kimi K2.5
LMArena Vision12691244Kimi K2.5
LMArena Text: English14531428Kimi K2.5
LMArena Text: non-English14331401Kimi K2.5
LMArena Text: Chinese14941463Kimi K2.5
LMArena Text: German14411425Kimi K2.5
LMArena Text: Japanese14231367Kimi K2.5
LMArena Text: Korean14121353Kimi K2.5
LMArena Text: French14541443Kimi K2.5
LMArena Text: Spanish14501425Kimi K2.5
LMArena Text: Russian14351400Kimi K2.5
LMArena Text: Polish14451398Kimi K2.5
LMArena Text: multi-turn14441416Kimi K2.5
LMArena Text: longer queries14451410Kimi K2.5
LMArena Text: writing and language14251387Kimi K2.5
LMArena Text: entertainment and media14171366Kimi K2.5
LMArena Vision: English12741249Kimi K2.5
LMArena Vision: Chinese13281301Kimi K2.5
LMArena Vision: reading text12761251Kimi K2.5
LMArena Vision: humor12841243Kimi K2.5
LMArena Vision: captioning1257Not measuredOnly Kimi K2.5 measured
LMArena Vision: recognizing things1285Not measuredOnly Kimi K2.5 measured
LMArena Vision: creative writing12691220Kimi K2.5
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Kimi K2.5 and Qwen3.5-122B-A10B
BenchmarkKimi K2.5Qwen3.5-122B-A10BLeader
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 K2.5$0.0018Fits in one request
Qwen3.5-122B-A10B$0.0013Fits in one request

Qwen3.5-122B-A10B costs less

Repository review

50K input + 3K output tokens

Kimi K2.5$0.033Fits in one request
Qwen3.5-122B-A10B$0.019Fits in one request

Qwen3.5-122B-A10B costs less

Agent loop

200K input + 10K output tokens

Kimi K2.5$0.125Fits in one request
Qwen3.5-122B-A10B$0.073Fits in one request

Qwen3.5-122B-A10B 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 K2.5 and Qwen3.5-122B-A10B
SpecificationMoonshotAI Kimi K2.5Qwen3.5-122B-A10B
MakerMoonshot AIQwen
WeightsOpen weightsOpen weights
ReleasedJanuary 27, 2026February 25, 2026
Context window262K262K
Input $/Mtok$0.50$0.26
Output $/Mtok$2.50$2.08
Coding index58.522.9
Independent measurements behind it21
Cost per solved task$0.24Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Kimi K2.5 better than Qwen3.5-122B-A10B for coding?

Pick Kimi K2.5 for coding: it scores 58.5 on the Vibe Coding Index against 22.9 for Qwen3.5-122B-A10B. Pick Qwen3.5-122B-A10B when output tokens cost 1.2x less, or when the benchmark that matters is IFBench, where it leads.

Which is cheaper, Kimi K2.5 or Qwen3.5-122B-A10B?

Kimi K2.5 costs $0.50 per million input tokens and $2.50 per million output tokens; Qwen3.5-122B-A10B costs $0.26 and $2.08. Cost per solved task is known for Kimi K2.5 only.

Which has the bigger context window, Kimi K2.5 or Qwen3.5-122B-A10B?

Neither: both take 262K tokens.

How many benchmarks is the Kimi K2.5 vs Qwen3.5-122B-A10B comparison based on?

47 benchmarks have a result for both models as of October 21, 2026. Kimi K2.5's coding index rests on 2 independent benchmarks and Qwen3.5-122B-A10B's on 1. Where only one model has a result, the page says so instead of naming a winner.

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