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Anthropic Claude Sonnet 4.5 VS MoonshotAI Kimi K2.7 Code

Claude Sonnet 4.5 vs Kimi K2.7 Code: which wins at real work?

22 task areas · same graded test runs · rank comparison only, so 0–100 and Elo collections never mix raw scores.

Kimi K2.7 Code wins 18 of 22 task areas we tested; Claude Sonnet 4.5 takes 4. Kimi K2.7 Code costs 4.2× less per token ($4.24 vs $18 per 1M).

4
Task areas won
18
58
Avg percentile
73
1
Top-3 finishes
0
$18.0
Price / 1M tokens
$4.24
Anthropic
Provider
MoonshotAI

Kimi K2.7 Code costs 4.2× less per token ($4.24 vs $18 per 1M).

Task by task

Task area Claude Sonnet 4.5 Kimi K2.7 Code Winner
Product & Project Management #71 / 110
Strong
#10 / 110
Excellent
Kimi K2.7 Code
Legal & HR #69 / 110
Strong
#14 / 110
Excellent
Kimi K2.7 Code
Summarization & Meeting Notes #2 / 110
Excellent
#47 / 110
Excellent
Claude Sonnet 4.5
Presentations & Decks #43 / 110
Excellent
#5 / 110
Excellent
Kimi K2.7 Code
Sales #10 / 110
Strong
#48 / 110
Usable
Claude Sonnet 4.5
Structured Output #80 / 113
Strong
#46 / 113
Excellent
Kimi K2.7 Code
Customer Support #43 / 113
Strong
#10 / 113
Strong
Kimi K2.7 Code
Investor & Pitch #42 / 66
Usable
#15 / 66
Strong
Kimi K2.7 Code
Content & Brand #74 / 124
Usable
#48 / 124
Strong
Kimi K2.7 Code
Executive Assistant #31 / 112
Strong
#6 / 112
Strong
Kimi K2.7 Code
Frontend & Landing Pages #29 / 109
Needs editing
#54 / 109
Needs editing
Claude Sonnet 4.5
AI Strategy #67 / 126
Strong
#44 / 126
Strong
Kimi K2.7 Code
Translation & Localization #25 / 110
Excellent
#48 / 110
Excellent
Claude Sonnet 4.5
Chef / Home Cooking #80 / 126
Usable
#58 / 126
Usable
Kimi K2.7 Code
Creative & Comedy #66 / 110 #44 / 110 Kimi K2.7 Code
Coding #62 / 115
Strong
#41 / 115
Strong
Kimi K2.7 Code
Research & Competitive Analysis #39 / 110
Strong
#20 / 110
Excellent
Kimi K2.7 Code
RAG, Safety & Grounding #39 / 113
Excellent
#21 / 113
Excellent
Kimi K2.7 Code
Landing Pages #30 / 72
Strong
#17 / 72
Strong
Kimi K2.7 Code
Knowledge & Docs #28 / 110
Strong
#16 / 110
Excellent
Kimi K2.7 Code
Training & Education #51 / 110
Excellent
#39 / 110
Excellent
Kimi K2.7 Code
Data & Analytics #33 / 110
Excellent
#31 / 110
Excellent
Kimi K2.7 Code

Rank = position among every model config we tested in that task area (lower is better). Sorted by biggest gap first.

Same task, both models — judged

Both models answered the same test case; an independent judge graded each. Quotes are the judge's actual rationale.

Presentations & Decks

Action titles from findings (Tradewinds) (Action Titles)
Claude Sonnet 4.5 6/100

“The response fails to use an Answer-First deductive structure and lacks a clear ask or next steps.”

Kimi K2.7 Code 100/100

“The response perfectly executes the prompt's requirements. It leads with strong, active-voice recommendations and builds a coherent, answer-first narrative across the three slides. The titles are excellent examples of executive-level action titles, and the supporting notes provide precise, non-redundant context.”

Frequently asked

Is Claude Sonnet 4.5 better than Kimi K2.7 Code?

Across 22 task areas we benchmarked, Kimi K2.7 Code ranks higher in 18 and Claude Sonnet 4.5 in 4.

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

Kimi K2.7 Code costs 4.2× less per token ($4.24 vs $18 per 1M).

What is Claude Sonnet 4.5 better at?

Claude Sonnet 4.5 out-ranks Kimi K2.7 Code at Summarization & Meeting Notes, Sales, Frontend & Landing Pages.

What is Kimi K2.7 Code better at?

Kimi K2.7 Code out-ranks Claude Sonnet 4.5 at Product & Project Management, Legal & HR, Presentations & Decks.

Full Claude Sonnet 4.5 review → Full Kimi K2.7 Code review → Full model leaderboard →

More comparisons

This page is Spring Prompt, running in public

We just did this for every model. Do it for your prompt.

The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.

  • Generate test cases from your prompt — no eval set required to start.
  • Compare models side by side with quality, cost and latency in one matrix.
  • Optimise the winner until the scores say it's ready to ship.
Experiment · Cold outreach email

Prompt × model results

12 test cases · 3 evals
Claude Opus
GPT-5
Gemini
v1
7.1
6.8
7.4
v2
8.3
7.9
8.0
v3
9.2
8.6
8.4
Best combo: v3 × Claude Opus
9.2 quality · $0.004/run · 1.8s