Model A

Anthropic

64.8/100

Estimated · Public rank #37

90% interval 50.5–79.1

Claude Sonnet 5 vs Kimi K2.7 Code

Updated August 14, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Model B

Kimi K2.7 Code

Moonshot AI

54.3/100

Estimated · Public rank #100

90% interval 42.8–65.9

Decision reading

Claude Sonnet 5 has the higher public score estimate, 64.78 versus 54.34, but the 90% score intervals overlap. Treat that as a lead, not a settled winner.

2 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

Long documents
Prompts that approach the documented context limit
Claude Sonnet 5
Claude Sonnet 5 has the larger documented context window.
Confidence: documented
Chat turn cost
1K fresh input + 500 output tokens
Kimi K2.7 Code
Kimi K2.7 Code has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Cache-heavy agent loop cost
200K cached + 20K fresh input + 10K output tokens
Claude Sonnet 5
Claude Sonnet 5 has the lower estimated token cost for this stated workload. Kimi K2.7 Code has no published cached-input rate, so cached tokens use its listed input rate.
Confidence: rate-fallback

Show secondary and unsupported calls

Repository review cost
50K fresh input + 3K output tokens
Kimi K2.7 Code
Kimi K2.7 Code has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.
Confidence: listed-rates
Coding work
Code generation, repair, and software-engineering tasks
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited
Agentic work
Tool use, computer use, and multi-step task completion
Not enough matched evidence
No shared weighted benchmark basis supports a winner.
Confidence: limited

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

17 Claude Sonnet 5 only

2 Shared

6 Kimi K2.7 Code only

Shared results: 2
Claude Sonnet 5 only: 17
Kimi K2.7 Code only: 6
Like-for-like categories: 0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable

Claude Sonnet 5: 81.9
Kimi K2.7 Code: Not measured
Weighted basis: 3 vs 0 rows
Reading: Not comparable

Coding

Not comparable

Claude Sonnet 5: 76.7
Kimi K2.7 Code: Not measured
Weighted basis: 2 vs 0 rows
Reading: Not comparable

Reasoning

Not comparable

Claude Sonnet 5: Not measured
Kimi K2.7 Code: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Knowledge

Not comparable

Claude Sonnet 5: 57.4
Kimi K2.7 Code: Not measured
Weighted basis: 1 vs 0 rows
Reading: Not comparable

Math

Not comparable

Claude Sonnet 5: Not measured
Kimi K2.7 Code: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Multilingual

Not comparable

Claude Sonnet 5: Not measured
Kimi K2.7 Code: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Multimodal

Not comparable

Claude Sonnet 5: 88.3
Kimi K2.7 Code: Not measured
Weighted basis: 1 vs 0 rows
Reading: Not comparable

Instruction following

Not comparable

Claude Sonnet 5: Not measured
Kimi K2.7 Code: Not measured
Weighted basis: 0 vs 0 rows
Reading: Not comparable

Category averages with the server-provided evidence basis for Claude Sonnet 5 and Kimi K2.7 Code
Category	Claude Sonnet 5	Kimi K2.7 Code	Weighted basis	Reading
Agentic	81.9	Not measured	Not comparable3 vs 0 rows	Not comparable
Coding	76.7	Not measured	Not comparable2 vs 0 rows	Not comparable
Reasoning	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Knowledge	57.4	Not measured	Not comparable1 vs 0 rows	Not comparable
Math	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Multilingual	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable
Multimodal	88.3	Not measured	Not comparable1 vs 0 rows	Not comparable
Instruction following	Not measured	Not measured	Not comparable0 vs 0 rows	Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Claude Sonnet 5: $0.007; Fits in one request
Kimi K2.7 Code: $0.00295; Fits in one request

Kimi K2.7 Code has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 5: $0.13; Fits in one request
Kimi K2.7 Code: $0.0595; Fits in one request

Kimi K2.7 Code has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Sonnet 5: $0.18; Fits in one request
Kimi K2.7 Code: $0.249; Fits in one request; Cached input priced at the published list-input rate

Claude Sonnet 5 has the lower modeled cost

Kimi K2.7 Code has no published cached-input rate, so cached tokens use its listed input rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

SpecificationClaude Sonnet 5Kimi K2.7 Code

Context window

Maximum documented context; output-token limits may be lower.

Claude Sonnet 5

Anthropic model overview

Kimi K2.7 Code

256K

API model ID

Claude Sonnet 5

claude-sonnet-5

Anthropic model overview

Kimi K2.7 Code

Not sourced

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Sonnet 5

$0.2 per 1M cached input tokens

Claude API pricing

Kimi K2.7 Code

Not published

Documented inputs

Claude Sonnet 5

text, image

Anthropic model overview

Kimi K2.7 Code

Not sourced

Documented outputs

Claude Sonnet 5

text

Anthropic model overview

Kimi K2.7 Code

Not sourced

Provider availability

Claude Sonnet 5

Generally Available · Claude API

Anthropic model overview

Kimi K2.7 Code

Not sourced

Reasoning profile

Claude Sonnet 5

Reasoning

Kimi K2.7 Code

Reasoning

Weight access

Claude Sonnet 5

Proprietary

Kimi K2.7 Code

Open Weight

License

Claude Sonnet 5

Proprietary

Kimi K2.7 Code

Open Weight

Release date

Claude Sonnet 5

2026-06-30

Kimi K2.7 Code

2026-06-12

If you already use one of these models

Deployment change: The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal: Claude Sonnet 5 has the higher public score estimate, 64.78 versus 54.34, but the 90% score intervals overlap.
Workload cost: Repository review: $0.13 vs $0.0595. Cache-heavy agent loop: $0.18 vs $0.249.
Context tradeoff: Claude Sonnet 5 has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

Claude Sonnet 5

API / mo$9,000

Self-host / moNot listed

Break-even—

Proprietary model — self-hosting not applicable.

Kimi K2.7 Code

API / mo$3,713

Self-host / mo$18,221

Break-even326M/day

Model the full break-even

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence25 rows

Agentic

Terminal-Bench 3.0
Claude Sonnet 514.6%
Source
Kimi K2.7 Code—
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%
Source
Kimi K2.7 Code—
Not directly comparable
BrowseComp
Claude Sonnet 584.7%
Source
Kimi K2.7 Code—
Not directly comparable
HLE w/ tools
Claude Sonnet 557.4%
Source
Kimi K2.7 Code—
Not directly comparable
OSWorld-Verified
Claude Sonnet 581.2%
Source
Kimi K2.7 Code—
Not directly comparable
Kimi Claw 24/7
Claude Sonnet 5—
Kimi K2.7 Code46.9%
Source
Not directly comparable
MCP Atlas
Claude Sonnet 5—
Kimi K2.7 Code76%
Source
Not directly comparable
MCP Mark Verified
Claude Sonnet 5—
Kimi K2.7 Code81.1%
Source
Not directly comparable

Coding

SWE-bench Verified
Claude Sonnet 585.2%
Source
Kimi K2.7 Code—
Not directly comparable
SWE-bench Pro
Claude Sonnet 563.2%
Source
Kimi K2.7 Code—
Not directly comparable
SWE Multilingual
Claude Sonnet 578.3%
Source
Kimi K2.7 Code—
Not directly comparable
SWE Multimodal
Claude Sonnet 528.1%
Source
Kimi K2.7 Code—
Not directly comparable
Terminal-Bench 2.0
Claude Sonnet 580.4%
Source
Kimi K2.7 Code—
Not directly comparable
FrontierCode 1.1 Main
Claude Sonnet 542.7%
Source
Kimi K2.7 Code—
Not directly comparable
cursorBench32
Shared source
Claude Sonnet 561.5%
Kimi K2.7 Code49.7%
Claude Sonnet 5 leads this result
APEX-SWE
Claude Sonnet 546.4%
Source
Kimi K2.7 Code—
Not directly comparable
EEBench
Shared source
Claude Sonnet 540.3%
Kimi K2.7 Code12.8%
Claude Sonnet 5 leads this result
3DCodeBench
Claude Sonnet 539.2%
Source
Kimi K2.7 Code—
Not directly comparable
Kimi Code Bench v2
Claude Sonnet 5—
Kimi K2.7 Code62.0%
Source
Not directly comparable
ProgramBench
Claude Sonnet 5—
Kimi K2.7 Code53.6%
Source
Not directly comparable
MLS-Bench Lite
Claude Sonnet 5—
Kimi K2.7 Code35.1%
Source
Not directly comparable

Knowledge

HLE
Claude Sonnet 557.4%
Source
Kimi K2.7 Code—
Not directly comparable
HLE w/o tools
Claude Sonnet 543.2%
Source
Kimi K2.7 Code—
Not directly comparable

Multimodal

CharXiv
Claude Sonnet 588.3%
Source
Kimi K2.7 Code—
Not directly comparable
CharXiv w/o tools
Claude Sonnet 577%
Source
Kimi K2.7 Code—
Not directly comparable

Frequently asked questions

Which is better, Claude Sonnet 5 or Kimi K2.7 Code?

Claude Sonnet 5 has the higher public score estimate, 64.78 versus 54.34, but the 90% score intervals overlap. The higher estimate is not a decisive winner because the uncertainty ranges overlap.

Which is better for coding, Claude Sonnet 5 or Kimi K2.7 Code?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Sonnet 5 or Kimi K2.7 Code?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Sonnet 5 or Kimi K2.7 Code?

For the stated presets, chat costs $0.007 on Claude Sonnet 5 and $0.00295 on Kimi K2.7 Code; repository review costs $0.13 and $0.0595; the cache-heavy agent loop costs $0.18 and $0.249. Kimi K2.7 Code has no published cached-input rate, so cached tokens use its listed input rate.

Which has the larger context window, Claude Sonnet 5 or Kimi K2.7 Code?

Claude Sonnet 5 has the larger documented context window: 1M, compared with 256K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated August 14, 2026

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Claude Sonnet 5 vs Kimi K2.7 Code

Which one for your work

Long documents

Chat turn cost

Cache-heavy agent loop cost

Repository review cost

Coding work

Agentic work

What is actually comparable

Category results, on a stated basis

Agentic

Coding

Reasoning

Knowledge

Math

Multilingual

Multimodal

Instruction following

Shape of the matched evidence

What each workload costs

Chat turn

Repository review

Cache-heavy agent loop

Specification differences

Context window

API model ID

Cached-input rate

Documented inputs

Documented outputs

Provider availability

Reasoning profile

Weight access

License

Release date

Self-host vs API cost

Benchmark evidence

Agentic

Coding

Knowledge

Multimodal

Frequently asked questions

Which is better, Claude Sonnet 5 or Kimi K2.7 Code?

Which is better for coding, Claude Sonnet 5 or Kimi K2.7 Code?

Which is better for agentic tasks, Claude Sonnet 5 or Kimi K2.7 Code?

Which costs less, Claude Sonnet 5 or Kimi K2.7 Code?

Which has the larger context window, Claude Sonnet 5 or Kimi K2.7 Code?

Related comparisons

Watch Claude Sonnet 5 vs Kimi K2.7 Code