Claude Haiku 4.5 vs Kimi K2.7 Code

Kimi K2.7 Code leads Claude Haiku 4.5 on coding, 53.4 to 35.6 on the Vibe Coding Index, and Kimi K2.7 Code costs 1.3x less per output token ($4.00 vs $5.00 per million). Updated October 21, 2026; 27 benchmarks have a result for both.

Replace Claude Haiku 4.5 Replace Kimi K2.7 Code

Claude Haiku 4.5Anthropic

Coding: 35.6
Overall: 41.0
Output $/M: $5.00

Kimi K2.7 CodeMoonshot AI

Coding: 53.4
Overall: 56.7
Output $/M: $4.00

vs boards won of 27 shared, 1 tied

Claude Haiku 4.5 or Kimi K2.7 Code: which to pick

Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 35.6 for Claude Haiku 4.5.

Claude Haiku 4.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Model AClaude Haiku 4.5Anthropic35.6/1004 independent benchmarks$0.56 per solved task Model BKimi K2.7 CodeMoonshot AI53.4/1004 independent benchmarks$0.35 per solved task

276824

Shared results: 27
Claude Haiku 4.5 only: 68
Kimi K2.7 Code only: 24
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.

Coding
Vibe Coding Index, six public coding benchmarks
Kimi K2.7 Code
Kimi K2.7 Code scores 53.4 against 35.6.
4 benchmarks behind each score
Intelligence
AA Intelligence Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 25.8 against 16.9.
Same board, both measured
Agentic work
AA Agentic Index
Kimi K2.7 Code
Kimi K2.7 Code leads, 21.0 against 8.0.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Claude Haiku 4.5 has a GPQA Diamond result, 72.2%.
Directional only
Math
AIME
No call
Only Claude Haiku 4.5 has a AIME result, 82.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Claude Haiku 4.5 has a MMLU Pro result, 78.7%.
Directional only
Web design
Design Arena: websites
Kimi K2.7 Code
Kimi K2.7 Code leads, 1264 against 1122.
Same board, both measured
Long documents
Listed context window
Kimi K2.7 Code
Kimi K2.7 Code takes 262K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.7 Code
Claude Haiku 4.5 $0.0035, Kimi K2.7 Code $0.0029 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.7 Code
Claude Haiku 4.5 $0.56, Kimi K2.7 Code $0.35.
Published attempt cost and pass rate

At a glance

Coding index: Claude Haiku 4.5 35.6 from 4 benchmarks, Kimi K2.7 Code 53.4 from 4 benchmarks.
Widest category: Math, 28.9 points apart on average over 1 shared benchmark.
Widest single gap: LiveCodeBench (Vals AI): Claude Haiku 4.5 41.2% against Kimi K2.7 Code 82.0%, 40.9 points apart on a 0 to 100 scale.
Output price: Claude Haiku 4.5 $5.00 against Kimi K2.7 Code $4.00 per million output tokens, 1.3x apart.
Context window: Claude Haiku 4.5 takes 200K 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
Category	Kimi K2.7 Code	Ties
Coding	10	1 tie
Intelligence	2
Agentic work	2
Reasoning	2
Math	1
Knowledge	1
Web design	8
All shared boards	26	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index010

Coding benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
SWE-bench Verified	66.6%	Not measured	Only Claude Haiku 4.5 measured
SWE-bench Multilingual	64.7%	Not measured	Only Claude Haiku 4.5 measured
LiveBench coding	48.1%	Not measured	Only Claude Haiku 4.5 measured
LMArena WebDev	1330	1474	Kimi K2.7 Code
AA Coding Index	43.9	60.8	Kimi K2.7 Code
LiveCodeBench (Vals AI)	41.2%	82.0%	Kimi K2.7 Code
SWE-bench Verified (Vals AI)	66.6%	78.2%	Kimi K2.7 Code
Vibe Code Bench (Vals AI)	11.4%	47.2%	Kimi K2.7 Code
Code migration (Vals AI)	7.5%	25.4%	Kimi K2.7 Code
ProgramBench (Vals AI)	0.0%	0.0%	Tie
Terminal-Bench 2.1 (Vals AI)	43.8%	67.0%	Kimi K2.7 Code
SkillsBench (Vals AI)	Not measured	50.0%	Only Kimi K2.7 Code measured
SciCode	Not measured	47.8%	Only Kimi K2.7 Code measured
Terminal-Bench Hard (Artificial Analysis run)	Not measured	44.7%	Only Kimi K2.7 Code measured
Terminal-Bench	35.5%	Not measured	Only Claude Haiku 4.5 measured
FrontierCode	Not measured	30.1%	Only Kimi K2.7 Code measured
WeirdML	45.4%	54.1%	Kimi K2.7 Code
ALE-Bench	Not measured	886.2	Only Kimi K2.7 Code measured
LMArena Text: coding	1454	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: software and IT	1439	Not measured	Only Claude Haiku 4.5 measured
LMArena WebDev: React	1326	1475	Kimi K2.7 Code
LMArena WebDev: HTML	1318	1451	Kimi K2.7 Code
LMArena WebDev: from an image	Not measured	1513	Only Kimi K2.7 Code measured
Neither model has a result on the other 16 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02

Intelligence benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
AA Intelligence Index	16.9	25.8	Kimi K2.7 Code
Epoch Capabilities Index	142.2	150.1	Kimi K2.7 Code

Agentic workLike-for-likePublic boards, shown as published, kept out of the index02

Agentic work benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
AA Agentic Index	8.0	21.0	Kimi K2.7 Code
Design Arena: agents building web apps	Not measured	1176	Only Kimi K2.7 Code measured
Design Arena: agents building full-stack apps	Not measured	1175	Only Kimi K2.7 Code measured
Design Arena: agents building mobile apps	Not measured	1143	Only Kimi K2.7 Code measured
Design Arena: agents building Android apps	Not measured	1137	Only Kimi K2.7 Code measured
Design Arena: agents building Godot games	Not measured	1147	Only Kimi K2.7 Code measured
Design Arena: agents building games	Not measured	1131	Only Kimi K2.7 Code measured
Design Arena: HTML slides	Not measured	1201	Only Kimi K2.7 Code measured
Design Arena: PowerPoint slides	Not measured	1154	Only Kimi K2.7 Code measured
LiveBench research	42.2%	Not measured	Only Claude Haiku 4.5 measured
LiveBench browser	40.0%	Not measured	Only Claude Haiku 4.5 measured
LiveBench long agentic	11.1%	Not measured	Only Claude Haiku 4.5 measured
Finance Agent (Vals AI)	31.0%	Not measured	Only Claude Haiku 4.5 measured
Tax Agent Bench (Vals AI)	5.9%	Not measured	Only Claude Haiku 4.5 measured
Legal Research Bench (Vals AI)	10.6%	Not measured	Only Claude Haiku 4.5 measured
Excel Modeling Benchmark (Vals AI)	22.7%	Not measured	Only Claude Haiku 4.5 measured
τ²-Bench Telecom	Not measured	90.1%	Only Kimi K2.7 Code measured
APEX-Agents	Not measured	37.6%	Only Kimi K2.7 Code measured
BALROG	31.2%	Not measured	Only Claude Haiku 4.5 measured
DeepResearch Bench	45.5%	Not measured	Only Claude Haiku 4.5 measured
Vending-Bench 2	$459	$5,083	Kimi K2.7 Code
Berkeley Function Calling Leaderboard (BFCL)	68.7%	Not measured	Only Claude Haiku 4.5 measured
Neither model has a result on the other 19 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index02

Reasoning benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
GPQA Diamond	72.2%	Not measured	Only Claude Haiku 4.5 measured
LiveBench reasoning	61.7%	Not measured	Only Claude Haiku 4.5 measured
MMMU Pro (Vals AI)	46.1%	Not measured	Only Claude Haiku 4.5 measured
GPQA Diamond (Artificial Analysis run)	Not measured	89.6%	Only Kimi K2.7 Code measured
Humanity's Last Exam (Artificial Analysis run)	Not measured	35.0%	Only Kimi K2.7 Code measured
GPQA Diamond (Epoch AI run)	71.2%	87.9%	Kimi K2.7 Code
ARC-AGI	47.7%	Not measured	Only Claude Haiku 4.5 measured
ARC-AGI-2	4.0%	Not measured	Only Claude Haiku 4.5 measured
SimpleBench	Not measured	57.9%	Only Kimi K2.7 Code measured
Chess puzzles	8.0%	14.0%	Kimi K2.7 Code
LMArena Text: hard prompts	1421	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: expert	1443	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: hard prompts in English	1435	Not measured	Only Claude Haiku 4.5 measured
Neither model has a result on the other 9 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index01

Math benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
AIME	82.7%	Not measured	Only Claude Haiku 4.5 measured
MGSM (Vals AI)	92.2%	Not measured	Only Claude Haiku 4.5 measured
OTIS Mock AIME	66.7%	95.6%	Kimi K2.7 Code
FrontierMath, tiers 1 to 3	Not measured	54.0%	Only Kimi K2.7 Code measured
FrontierMath, tier 4	Not measured	12.2%	Only Kimi K2.7 Code measured
MATH level 5	96.4%	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: math	1398	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: mathematical work	1430	Not measured	Only Claude Haiku 4.5 measured
Neither model has a result on the other 5 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01

Knowledge benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
MMLU Pro	78.7%	Not measured	Only Claude Haiku 4.5 measured
LegalBench (Vals AI)	81.2%	Not measured	Only Claude Haiku 4.5 measured
CaseLaw (Vals AI)	56.5%	Not measured	Only Claude Haiku 4.5 measured
CorpFin (Vals AI)	60.6%	Not measured	Only Claude Haiku 4.5 measured
TaxEval (Vals AI)	67.5%	Not measured	Only Claude Haiku 4.5 measured
MortgageTax (Vals AI)	62.2%	Not measured	Only Claude Haiku 4.5 measured
MedQA (Vals AI)	79.6%	Not measured	Only Claude Haiku 4.5 measured
MedCode (Vals AI)	32.7%	Not measured	Only Claude Haiku 4.5 measured
SimpleQA Verified	13.2%	36.5%	Kimi K2.7 Code
LMArena Text: science	1406	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: medicine and healthcare	1394	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: legal and government	1400	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: business and finance	1400	Not measured	Only Claude Haiku 4.5 measured
Neither model has a result on the other 5 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index08

Web design benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
Design Arena: websites	1122	1264	Kimi K2.7 Code
Design Arena: UI components	1100	1259	Kimi K2.7 Code
Design Arena: game dev	1097	1220	Kimi K2.7 Code
Design Arena: data viz	1124	1227	Kimi K2.7 Code
Design Arena: 3D	1072	1241	Kimi K2.7 Code
Design Arena: all code categories	1115	1253	Kimi K2.7 Code
Design Arena: SVG	1026	1176	Kimi K2.7 Code
Design Arena: ASCII art	1140	1196	Kimi K2.7 Code
LiveBench design	59.9%	Not measured	Only Claude Haiku 4.5 measured

GeneralDirectional onlyPublic boards, shown as published, kept out of the index29 boards, none shared

General benchmarks for Claude Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
LiveBench data analysis	59.3%	Not measured	Only Claude Haiku 4.5 measured
Public Benefits Bench (Vals AI)	54.3%	Not measured	Only Claude Haiku 4.5 measured
SAGE (Vals AI)	31.8%	Not measured	Only Claude Haiku 4.5 measured
MedScribe (Vals AI)	85.2%	Not measured	Only Claude Haiku 4.5 measured
Vals Multimodal Index	42.9%	Not measured	Only Claude Haiku 4.5 measured
IFBench	Not measured	63.1%	Only Kimi K2.7 Code measured
Long context reasoning (AA-LCR)	Not measured	79.3%	Only Kimi K2.7 Code measured
DTBench	73.6%	Not measured	Only Claude Haiku 4.5 measured
LMCA	30.9%	Not measured	Only Claude Haiku 4.5 measured
Surface Evolver Bench	Not measured	48.8%	Only Kimi K2.7 Code measured
ExploitBench	13.7%	Not measured	Only Claude Haiku 4.5 measured
LMArena Text	1397	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: instruction following	1414	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: creative writing	1371	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: English	1414	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: non-English	1377	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: Chinese	1418	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: German	1374	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: Japanese	1338	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: Korean	1346	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: French	1411	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: Spanish	1421	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: Russian	1381	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: Polish	1343	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: multi-turn	1409	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: longer queries	1427	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: writing and language	1386	Not measured	Only Claude Haiku 4.5 measured
LMArena Text: entertainment and media	1369	Not measured	Only Claude Haiku 4.5 measured
LMArena Document	1420	Not measured	Only Claude Haiku 4.5 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 Haiku 4.5 and Kimi K2.7 Code
Benchmark	Claude Haiku 4.5	Kimi K2.7 Code	Leader
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 Haiku 4.5$0.0035Fits 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 Haiku 4.5$0.065Fits 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 Haiku 4.5$0.250Exceeds the context window

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 Haiku 4.5 and Kimi K2.7 Code
Specification	Anthropic Claude Haiku 4.5	MoonshotAI Kimi K2.7 Code
Maker	Anthropic	Moonshot AI
Weights	No public weights listed	Open weights
Released	October 15, 2025	June 12, 2026
Context window	200K	262K
Input $/Mtok	$1.00	$0.95
Output $/Mtok	$5.00	$4.00
Coding index	35.6	53.4
Independent measurements behind it	4	4
Cost per solved task	$0.56	$0.35
Source	OpenRouter listing	OpenRouter listing

Questions

Is Claude Haiku 4.5 better than Kimi K2.7 Code for coding?

Pick Kimi K2.7 Code for coding: it scores 53.4 on the Vibe Coding Index against 35.6 for Claude Haiku 4.5. Claude Haiku 4.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.

Which is cheaper, Claude Haiku 4.5 or Kimi K2.7 Code?

Claude Haiku 4.5 costs $1.00 per million input tokens and $5.00 per million output tokens; Kimi K2.7 Code costs $0.95 and $4.00. Per solved SWE-bench Verified task, Claude Haiku 4.5 costs $0.56 and Kimi K2.7 Code $0.35.

Which has the bigger context window, Claude Haiku 4.5 or Kimi K2.7 Code?

Kimi K2.7 Code, with 262K tokens against 200K.

How many benchmarks is the Claude Haiku 4.5 vs Kimi K2.7 Code comparison based on?

27 benchmarks have a result for both models as of October 21, 2026. Claude Haiku 4.5's coding index rests on 4 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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Claude Haiku 4.5 or Kimi K2.7 Code: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next