Enter opens the highlighted result. Esc closes.

Kimi K2 0905 vs Kimi K2.5

Kimi K2.5 leads Kimi K2 0905 on the Artificial Analysis Intelligence Index, 23.5 to 15.3, at about the same output price ($2.85 vs $2.50 per million). Updated October 21, 2026; 13 benchmarks have a result for both.

Kimi K2 0905Moonshot AI
Coding
No data
Overall
No data
Output $/M
$2.50
0
Kimi K2.5Moonshot AI
Coding
38.6
Overall
44.8
Output $/M
$2.85
13
vs boards won of 13 shared

Kimi K2 0905 or Kimi K2.5: which to pick

Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; Kimi K2 0905 has none, so the two cannot be ranked on coding.

Pick Kimi K2 0905 for output tokens 1.1x cheaper ($2.50 vs $2.85 per million).

Shared results
13
Kimi K2 0905 only
4
Kimi K2.5 only
86
Like-for-like categories
6 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 0905 not benchmarked, Kimi K2.5 38.6 from 3 benchmarks.
Widest category
General, 24.3 points apart on average over 3 shared benchmarks.
Widest single gap
IFBench: Kimi K2 0905 41.7% against Kimi K2.5 70.2%, 28.5 points apart on a 0 to 100 scale.
Output price
Kimi K2 0905 $2.50 against Kimi K2.5 $2.85 per million output tokens, 1.1x 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 0905BarsKimi K2.5Ties
Coding03
Intelligence01
Agentic work01
Reasoning03
Web design02
General03
All shared boards013
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
SWE-bench VerifiedNot measured70.8%Only Kimi K2.5 measured
SWE-bench MultilingualNot measured67.3%Only Kimi K2.5 measured
LMArena WebDevNot measured1437Only Kimi K2.5 measured
AA Coding IndexNot measured46.8Only Kimi K2.5 measured
LiveCodeBench (Vals AI)Not measured83.9%Only Kimi K2.5 measured
SWE-bench Verified (Vals AI)Not measured70.0%Only Kimi K2.5 measured
Vibe Code Bench (Vals AI)Not measured17.5%Only Kimi K2.5 measured
Code migration (Vals AI)Not measured7.0%Only Kimi K2.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured42.0%Only Kimi K2.5 measured
LiveCodeBench (Artificial Analysis run)61.0%Not measuredOnly Kimi K2 0905 measured
Terminal-Bench Hard (Artificial Analysis run)23.5%34.8%Kimi K2.5
Terminal-BenchNot measured43.2%Only Kimi K2.5 measured
WeirdML36.7%45.6%Kimi K2.5
ALE-Bench267.1821.6Kimi K2.5
LMArena Text: codingNot measured1483Only Kimi K2.5 measured
LMArena Text: software and ITNot measured1471Only Kimi K2.5 measured
LMArena WebDev: ReactNot measured1429Only Kimi K2.5 measured
LMArena WebDev: HTMLNot measured1426Only Kimi K2.5 measured
LMArena WebDev: from an imageNot measured1439Only Kimi K2.5 measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
AA Intelligence Index15.323.5Kimi K2.5
Epoch Capabilities IndexNot measured148.1Only Kimi K2.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
Design Arena: agents building web appsNot measured1136Only Kimi K2.5 measured
Design Arena: agents building full-stack appsNot measured1114Only Kimi K2.5 measured
Design Arena: agents building mobile appsNot measured1147Only Kimi K2.5 measured
Design Arena: agents building Android appsNot measured1118Only Kimi K2.5 measured
Design Arena: agents building Godot gamesNot measured1219Only Kimi K2.5 measured
Finance Agent (Vals AI)Not measured35.8%Only Kimi K2.5 measured
Legal Research Bench (Vals AI)Not measured15.9%Only Kimi K2.5 measured
Excel Modeling Benchmark (Vals AI)Not measured28.5%Only Kimi K2.5 measured
τ²-Bench Telecom73.4%95.9%Kimi K2.5
OSWorldNot measured63.3%Only Kimi K2.5 measured
Vending-Bench 2Not measured$1,198Only Kimi K2.5 measured
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index03
Reasoning benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
GPQA DiamondNot measured84.1%Only Kimi K2.5 measured
MMMU Pro (Vals AI)Not measured84.3%Only Kimi K2.5 measured
GPQA Diamond (Artificial Analysis run)76.7%87.9%Kimi K2.5
Humanity's Last Exam (Artificial Analysis run)6.4%30.7%Kimi K2.5
ARC-AGINot measured65.3%Only Kimi K2.5 measured
ARC-AGI-2Not measured11.8%Only Kimi K2.5 measured
SimpleBenchNot measured46.8%Only Kimi K2.5 measured
LMArena Text: hard promptsNot measured1453Only Kimi K2.5 measured
LMArena Text: expertNot measured1466Only Kimi K2.5 measured
LMArena Text: hard prompts in EnglishNot measured1460Only Kimi K2.5 measured
LMArena Vision: diagramsNot measured1282Only Kimi K2.5 measured
LMArena Vision: homeworkNot measured1297Only Kimi K2.5 measured
Kagi LLM Benchmark52.2%78.5%Kimi K2.5
Neither model has a result on the other 9 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index5 boards, none shared
Math benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
AIMENot measured95.6%Only Kimi K2.5 measured
AA Math Index57.3Not measuredOnly Kimi K2 0905 measured
AIME 2025 (Artificial Analysis run)57.3%Not measuredOnly Kimi K2 0905 measured
LMArena Text: mathNot measured1470Only Kimi K2.5 measured
LMArena Text: mathematical workNot measured1473Only Kimi K2.5 measured
Neither model has a result on the other 8 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
Knowledge benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
MMLU ProNot measured85.9%Only Kimi K2.5 measured
CaseLaw (Vals AI)Not measured58.7%Only Kimi K2.5 measured
CorpFin (Vals AI)Not measured68.3%Only Kimi K2.5 measured
TaxEval (Vals AI)Not measured74.2%Only Kimi K2.5 measured
MortgageTax (Vals AI)Not measured66.5%Only Kimi K2.5 measured
MedQA (Vals AI)Not measured94.4%Only Kimi K2.5 measured
MedCode (Vals AI)Not measured39.3%Only Kimi K2.5 measured
MMLU Pro (Artificial Analysis run)81.9%Not measuredOnly Kimi K2 0905 measured
SimpleQA VerifiedNot measured34.3%Only Kimi K2.5 measured
LMArena Text: scienceNot measured1459Only Kimi K2.5 measured
LMArena Text: medicine and healthcareNot measured1448Only Kimi K2.5 measured
LMArena Text: legal and governmentNot measured1441Only Kimi K2.5 measured
LMArena Text: business and financeNot measured1427Only Kimi K2.5 measured
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index02
Web design benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
Design Arena: websites10891248Kimi K2.5
Design Arena: UI componentsNot measured1236Only Kimi K2.5 measured
Design Arena: game devNot measured1207Only Kimi K2.5 measured
Design Arena: data vizNot measured1219Only Kimi K2.5 measured
Design Arena: 3DNot measured1205Only Kimi K2.5 measured
Design Arena: all code categories10981236Kimi K2.5
Design Arena: SVGNot measured1149Only Kimi K2.5 measured
Design Arena: ASCII artNot measured1166Only 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 index03
General benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
SAGE (Vals AI)Not measured49.9%Only Kimi K2.5 measured
MedScribe (Vals AI)Not measured76.4%Only Kimi K2.5 measured
IFBench41.7%70.2%Kimi K2.5
Long context reasoning (AA-LCR)53.0%78.0%Kimi K2.5
Fiction.LiveBench66.7%86.1%Kimi K2.5
CL-benchNot measured19.3%Only Kimi K2.5 measured
CL-bench LifeNot measured13.2%Only Kimi K2.5 measured
LMArena TextNot measured1445Only Kimi K2.5 measured
LMArena Text: instruction followingNot measured1431Only Kimi K2.5 measured
LMArena Text: creative writingNot measured1422Only Kimi K2.5 measured
LMArena VisionNot measured1269Only Kimi K2.5 measured
LMArena Text: EnglishNot measured1453Only Kimi K2.5 measured
LMArena Text: non-EnglishNot measured1433Only Kimi K2.5 measured
LMArena Text: ChineseNot measured1494Only Kimi K2.5 measured
LMArena Text: GermanNot measured1441Only Kimi K2.5 measured
LMArena Text: JapaneseNot measured1423Only Kimi K2.5 measured
LMArena Text: KoreanNot measured1412Only Kimi K2.5 measured
LMArena Text: FrenchNot measured1454Only Kimi K2.5 measured
LMArena Text: SpanishNot measured1450Only Kimi K2.5 measured
LMArena Text: RussianNot measured1435Only Kimi K2.5 measured
LMArena Text: PolishNot measured1445Only Kimi K2.5 measured
LMArena Text: multi-turnNot measured1444Only Kimi K2.5 measured
LMArena Text: longer queriesNot measured1445Only Kimi K2.5 measured
LMArena Text: writing and languageNot measured1425Only Kimi K2.5 measured
LMArena Text: entertainment and mediaNot measured1417Only Kimi K2.5 measured
LMArena Vision: EnglishNot measured1274Only Kimi K2.5 measured
LMArena Vision: ChineseNot measured1328Only Kimi K2.5 measured
LMArena Vision: reading textNot measured1276Only Kimi K2.5 measured
LMArena Vision: humorNot measured1284Only Kimi K2.5 measured
LMArena Vision: captioningNot measured1257Only Kimi K2.5 measured
LMArena Vision: recognizing thingsNot measured1285Only Kimi K2.5 measured
LMArena Vision: creative writingNot measured1269Only Kimi K2.5 measured
Neither model has a result on the other 14 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Kimi K2 0905 and Kimi K2.5
BenchmarkKimi K2 0905Kimi K2.5Leader
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 0905$0.0019Fits in one request
Kimi K2.5$0.0020Fits in one request

Kimi K2 0905 costs less

Repository review

50K input + 3K output tokens

Kimi K2 0905$0.037Fits in one request
Kimi K2.5$0.035Fits in one request

Kimi K2.5 costs less

Agent loop

200K input + 10K output tokens

Kimi K2 0905$0.145Fits in one request
Kimi K2.5$0.135Fits in one request

Kimi K2.5 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 0905 and Kimi K2.5
SpecificationMoonshotAI Kimi K2 0905MoonshotAI Kimi K2.5
MakerMoonshot AIMoonshot AI
WeightsOpen weightsOpen weights
ReleasedSeptember 4, 2025January 27, 2026
Context window262K262K
Input $/Mtok$0.60$0.532
Output $/Mtok$2.50$2.85
Coding indexNot benchmarked38.6
Independent measurements behind it03
Cost per solved taskNot computable$0.24
SourceOpenRouter listingOpenRouter listing

Questions

Is Kimi K2 0905 better than Kimi K2.5 for coding?

Only Kimi K2.5 has a coding score, 38.6 on the Vibe Coding Index; Kimi K2 0905 has none, so the two cannot be ranked on coding. Pick Kimi K2 0905 for output tokens 1.1x cheaper ($2.50 vs $2.85 per million).

Which is cheaper, Kimi K2 0905 or Kimi K2.5?

Kimi K2 0905 costs $0.60 per million input tokens and $2.50 per million output tokens; Kimi K2.5 costs $0.532 and $2.85. Cost per solved task is known for Kimi K2.5 only.

Which has the bigger context window, Kimi K2 0905 or Kimi K2.5?

Neither: both take 262K tokens.

How many benchmarks is the Kimi K2 0905 vs Kimi K2.5 comparison based on?

13 benchmarks have a result for both models as of October 21, 2026. Kimi K2 0905's coding index rests on 0 independent benchmarks and Kimi K2.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

Compare next