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Claude Opus 5.5 vs Kimi K2.7 Code

Claude Opus 5.5 leads Kimi K2.7 Code on coding, 88.8 to 53.4 on the Vibe Coding Index, and Kimi K2.7 Code costs 5.0x less per output token ($4.00 vs $20.00 per million). Updated October 22, 2026; 32 benchmarks have a result for both.

Claude Opus 5.5Anthropic
Coding
88.8
Overall
87.1
Output $/M
$20.00
32
Kimi K2.7 CodeMoonshot AI
Coding
53.4
Overall
56.7
Output $/M
$4.00
0
vs boards won of 32 shared

Claude Opus 5.5 or Kimi K2.7 Code: which to pick

Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 53.4 for Kimi K2.7 Code.

Pick Kimi K2.7 Code for output tokens 5.0x cheaper ($4.00 vs $20.00 per million).

Shared results
32
Claude Opus 5.5 only
77
Kimi K2.7 Code only
19
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
Claude Opus 5.5 88.8 from 5 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category
Math, 41.5 points apart on average over 3 shared benchmarks.
Widest single gap
FrontierMath, tier 4: Claude Opus 5.5 95.0% against Kimi K2.7 Code 12.2%, 82.8 points apart on a 0 to 100 scale.
Output price
Claude Opus 5.5 $20.00 against Kimi K2.7 Code $4.00 per million output tokens, 5.0x apart.
Context window
Claude Opus 5.5 takes 1M tokens, Kimi K2.7 Code 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
CategoryClaude Opus 5.5BarsKimi K2.7 CodeTies
Coding110
Intelligence20
Agentic work40
Reasoning30
Math30
Knowledge10
Web design70
General10
All shared boards320
CodingLike-for-likeSix of these boards feed the Vibe Coding Index110
Coding benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
LiveBench coding96.3%Not measuredOnly Claude Opus 5.5 measured
LMArena WebDev18071474Claude Opus 5.5
AA Coding IndexNot measured60.8Only Kimi K2.7 Code measured
LiveCodeBench (Vals AI)Not measured82.0%Only Kimi K2.7 Code measured
SWE-bench Verified (Vals AI)Not measured78.2%Only Kimi K2.7 Code measured
Terminal-Bench 4 (Vals AI)65.2%Not measuredOnly Claude Opus 5.5 measured
Vibe Code Bench (Vals AI)90.3%47.2%Claude Opus 5.5
Code migration (Vals AI)66.7%25.4%Claude Opus 5.5
ProgramBench (Vals AI)18.5%0.0%Claude Opus 5.5
IOI (Vals AI)95.1%Not measuredOnly Claude Opus 5.5 measured
Terminal-Bench 2.1 (Vals AI)87.6%67.0%Claude Opus 5.5
SWE-bench Multimodal (Vals AI)70.2%Not measuredOnly Claude Opus 5.5 measured
Vibe Code Bench 1-100 (Vals AI)30.4%Not measuredOnly Claude Opus 5.5 measured
SkillsBench (Vals AI)Not measured50.0%Only Kimi K2.7 Code measured
CyberBench (Vals AI)74.6%Not measuredOnly Claude Opus 5.5 measured
SciCode66.9%47.8%Claude Opus 5.5
Terminal-Bench Hard (Artificial Analysis run)Not measured44.7%Only Kimi K2.7 Code measured
FrontierCode54.6%30.1%Claude Opus 5.5
FrontierSWE62.3%Not measuredOnly Claude Opus 5.5 measured
WeirdMLNot measured54.1%Only Kimi K2.7 Code measured
MirrorCode77.4%Not measuredOnly Claude Opus 5.5 measured
ALE-Bench2147.4886.2Claude Opus 5.5
LMArena Text: coding1545Not measuredOnly Claude Opus 5.5 measured
LMArena Text: software and IT1538Not measuredOnly Claude Opus 5.5 measured
LMArena WebDev: React18551475Claude Opus 5.5
LMArena WebDev: HTML17531451Claude Opus 5.5
LMArena WebDev: from an image17531513Claude Opus 5.5
SciCode18.5%Not measuredOnly Claude Opus 5.5 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 Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
AA Intelligence Index57.625.8Claude Opus 5.5
Epoch Capabilities Index168.8150.1Claude Opus 5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
Agentic work benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
AA Agentic IndexNot measured21.0Only Kimi K2.7 Code measured
Design Arena: agents building web apps13161176Claude Opus 5.5
Design Arena: agents building full-stack appsNot measured1175Only Kimi K2.7 Code measured
Design Arena: agents building mobile apps13091143Claude Opus 5.5
Design Arena: agents building Android appsNot measured1138Only Kimi K2.7 Code measured
Design Arena: agents building Godot gamesNot measured1147Only Kimi K2.7 Code measured
Design Arena: agents building gamesNot measured1130Only Kimi K2.7 Code measured
Design Arena: HTML slidesNot measured1151Only Kimi K2.7 Code measured
Design Arena: PowerPoint slidesNot measured1130Only Kimi K2.7 Code measured
Design Arena: spreadsheets1386Not measuredOnly Claude Opus 5.5 measured
LiveBench research85.0%Not measuredOnly Claude Opus 5.5 measured
LiveBench browser80.0%Not measuredOnly Claude Opus 5.5 measured
LiveBench long agentic85.0%Not measuredOnly Claude Opus 5.5 measured
SREBench (Vals AI)33.6%Not measuredOnly Claude Opus 5.5 measured
Finance Agent (Vals AI)58.6%Not measuredOnly Claude Opus 5.5 measured
Tax Agent Bench (Vals AI)45.6%Not measuredOnly Claude Opus 5.5 measured
Legal Research Bench (Vals AI)50.5%Not measuredOnly Claude Opus 5.5 measured
Harvey's Legal Agent Benchmark (Vals AI)9.2%Not measuredOnly Claude Opus 5.5 measured
Excel Modeling Benchmark (Vals AI)75.9%Not measuredOnly Claude Opus 5.5 measured
BioMysteryBench (Vals AI)79.3%Not measuredOnly Claude Opus 5.5 measured
Terminal-Bench-Science (Vals AI)47.1%Not measuredOnly Claude Opus 5.5 measured
Vals Science Index58.7%Not measuredOnly Claude Opus 5.5 measured
Time Horizon Index (Vals AI)91.3%Not measuredOnly Claude Opus 5.5 measured
CUA-bench (Vals AI)14.0%Not measuredOnly Claude Opus 5.5 measured
Robo-bench (Vals AI)14.6%Not measuredOnly Claude Opus 5.5 measured
τ²-Bench TelecomNot measured90.1%Only Kimi K2.7 Code measured
APEX-Agents73.5%37.6%Claude Opus 5.5
Remote Labor Index21.3%Not measuredOnly Claude Opus 5.5 measured
SpireClimb3.3%Not measuredOnly Claude Opus 5.5 measured
Vending-Bench 2$9,235$5,083Claude Opus 5.5
LMArena Search1213Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 10 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index30
Reasoning benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
LiveBench reasoning92.2%Not measuredOnly Claude Opus 5.5 measured
MysteryMechanism (Vals AI)49.5%Not measuredOnly Claude Opus 5.5 measured
GPQA Diamond (Artificial Analysis run)Not measured89.6%Only Kimi K2.7 Code measured
Humanity's Last Exam (Artificial Analysis run)61.4%35.0%Claude Opus 5.5
GPQA Diamond (Epoch AI run)90.6%87.9%Claude Opus 5.5
ARC-AGI98.5%Not measuredOnly Claude Opus 5.5 measured
ARC-AGI-293.3%Not measuredOnly Claude Opus 5.5 measured
SimpleBenchNot measured57.9%Only Kimi K2.7 Code measured
Chess puzzles67.0%14.0%Claude Opus 5.5
Mystery game puzzles71.0%Not measuredOnly Claude Opus 5.5 measured
EBR-bench71.4%Not measuredOnly Claude Opus 5.5 measured
LMArena Text: hard prompts1536Not measuredOnly Claude Opus 5.5 measured
LMArena Text: expert1549Not measuredOnly Claude Opus 5.5 measured
LMArena Text: hard prompts in English1535Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: diagrams1345Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: homework1362Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
OTIS Mock AIME100.0%95.6%Claude Opus 5.5
FrontierMath, tiers 1 to 391.2%54.0%Claude Opus 5.5
FrontierMath, tier 495.0%12.2%Claude Opus 5.5
ProofBench100.0%Not measuredOnly Claude Opus 5.5 measured
LMArena Text: math1518Not measuredOnly Claude Opus 5.5 measured
LMArena Text: mathematical work1516Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
MedCode (Vals AI)49.8%Not measuredOnly Claude Opus 5.5 measured
SimpleQA Verified72.2%36.5%Claude Opus 5.5
LMArena Text: science1524Not measuredOnly Claude Opus 5.5 measured
LMArena Text: medicine and healthcare1509Not measuredOnly Claude Opus 5.5 measured
LMArena Text: legal and government1518Not measuredOnly Claude Opus 5.5 measured
LMArena Text: business and finance1494Not measuredOnly Claude Opus 5.5 measured
FACTS Benchmark Suite65.3%Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
Design Arena: websites13351264Claude Opus 5.5
Design Arena: UI components13821255Claude Opus 5.5
Design Arena: game dev14551219Claude Opus 5.5
Design Arena: data viz13981227Claude Opus 5.5
Design Arena: 3D14761240Claude Opus 5.5
Design Arena: all code categories13881252Claude Opus 5.5
Design Arena: SVG13281176Claude Opus 5.5
Design Arena: ASCII artNot measured1196Only Kimi K2.7 Code measured
LiveBench design86.9%Not measuredOnly Claude Opus 5.5 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
Vals Index70.2%Not measuredOnly Claude Opus 5.5 measured
LiveBench data analysis80.3%Not measuredOnly Claude Opus 5.5 measured
Public Benefits Bench (Vals AI)70.6%Not measuredOnly Claude Opus 5.5 measured
SAGE (Vals AI)45.8%Not measuredOnly Claude Opus 5.5 measured
MedScribe (Vals AI)91.4%Not measuredOnly Claude Opus 5.5 measured
IFBenchNot measured63.1%Only Kimi K2.7 Code measured
Long context reasoning (AA-LCR)84.7%79.3%Claude Opus 5.5
DTBench98.9%Not measuredOnly Claude Opus 5.5 measured
LMCA68.2%Not measuredOnly Claude Opus 5.5 measured
Surface Evolver BenchNot measured48.8%Only Kimi K2.7 Code measured
Furniture assembly83.3%Not measuredOnly Claude Opus 5.5 measured
LMArena Text1516Not measuredOnly Claude Opus 5.5 measured
LMArena Text: instruction following1537Not measuredOnly Claude Opus 5.5 measured
LMArena Text: creative writing1535Not measuredOnly Claude Opus 5.5 measured
LMArena Vision1321Not measuredOnly Claude Opus 5.5 measured
LMArena Text: English1519Not measuredOnly Claude Opus 5.5 measured
LMArena Text: non-English1507Not measuredOnly Claude Opus 5.5 measured
LMArena Text: Chinese1582Not measuredOnly Claude Opus 5.5 measured
LMArena Text: Japanese1534Not measuredOnly Claude Opus 5.5 measured
LMArena Text: French1493Not measuredOnly Claude Opus 5.5 measured
LMArena Text: Spanish1508Not measuredOnly Claude Opus 5.5 measured
LMArena Text: Russian1517Not measuredOnly Claude Opus 5.5 measured
LMArena Text: multi-turn1501Not measuredOnly Claude Opus 5.5 measured
LMArena Text: longer queries1532Not measuredOnly Claude Opus 5.5 measured
LMArena Text: writing and language1532Not measuredOnly Claude Opus 5.5 measured
LMArena Text: entertainment and media1515Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: English1317Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: reading text1326Not measuredOnly Claude Opus 5.5 measured
LMArena Vision: creative writing1320Not measuredOnly Claude Opus 5.5 measured
Neither model has a result on the other 17 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Claude Opus 5.5 and Kimi K2.7 Code
BenchmarkClaude Opus 5.5Kimi K2.7 CodeLeader
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

Claude Opus 5.5$0.014Fits in one request
Kimi K2.7 Code$0.0029Fits in one request

Kimi K2.7 Code costs less

Repository review

50K input + 3K output tokens

Claude Opus 5.5$0.260Fits in one request
Kimi K2.7 Code$0.059Fits in one request

Kimi K2.7 Code costs less

Agent loop

200K input + 10K output tokens

Claude Opus 5.5$1.00Fits in one request
Kimi K2.7 Code$0.230Fits in one request

Kimi K2.7 Code 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 Claude Opus 5.5 and Kimi K2.7 Code
SpecificationAnthropic Claude Opus 5.5MoonshotAI Kimi K2.7 Code
MakerAnthropicMoonshot AI
WeightsNo public weights listedOpen weights
ReleasedSeptember 22, 2026June 12, 2026
Context window1M262K
Input $/Mtok$4.00$0.95
Output $/Mtok$20.00$4.00
Coding index88.853.4
Independent measurements behind it54
Cost per solved taskNot computable$0.35
SourceOpenRouter listingOpenRouter listing

Questions

Is Claude Opus 5.5 better than Kimi K2.7 Code for coding?

Pick Claude Opus 5.5 for coding: it scores 88.8 on the Vibe Coding Index against 53.4 for Kimi K2.7 Code. Pick Kimi K2.7 Code for output tokens 5.0x cheaper ($4.00 vs $20.00 per million).

Which is cheaper, Claude Opus 5.5 or Kimi K2.7 Code?

Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Cost per solved task is known for Kimi K2.7 Code only.

Which has the bigger context window, Claude Opus 5.5 or Kimi K2.7 Code?

Claude Opus 5.5, with 1M tokens against 262K.

How many benchmarks is the Claude Opus 5.5 vs Kimi K2.7 Code comparison based on?

32 benchmarks have a result for both models as of October 22, 2026. Claude Opus 5.5's coding index rests on 5 independent benchmarks and Kimi K2.7 Code's on 4. Where only one model has a result, the page says so instead of naming a winner.

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