Last verified 2026-03-12 (left) · 2025-09-22 (right)

Kimi K2.5 vs Claude Sonnet 3.7 (Legacy) — Pricing & Capability Comparison

Kimi K2.5 charges $0.60 per million input tokens and $3.00 per million output tokens. Claude Sonnet 3.7 (Legacy) comes in at $3.00 / $15.00. Context windows span 262K vs 200K tokens respectively.

TL;DR — Quick Comparison

✓Kimi K2.5 is cheaper overall: $3.60 per 1M tokens (in+out) vs $18.00 for Claude Sonnet 3.7 (Legacy) — saves $14.40 per 1M tokens
✓Input pricing: Kimi K2.5 $0.60/1M vs Claude Sonnet 3.7 (Legacy) $3.00/1M
✓Output pricing: Kimi K2.5 $3.00/1M vs Claude Sonnet 3.7 (Legacy) $15.00/1M
✓Context window: Kimi K2.5 offers more (262K vs 200K)
✓Use our calculator below to estimate costs for your specific usage pattern

Input price (per 1M)

Kimi K2.5

$0.60

Claude Sonnet 3.7 (Legacy)

$3.00

Kimi K2.5 leads here

Output price (per 1M)

Kimi K2.5

$3.00

Claude Sonnet 3.7 (Legacy)

$15.00

Kimi K2.5 leads here

Context window

Kimi K2.5

262,144 tokens

Claude Sonnet 3.7 (Legacy)

200,000 tokens

Kimi K2.5 leads here

Cached input

Kimi K2.5

$0.100

Claude Sonnet 3.7 (Legacy)

Not published

Kimi K2.5 leads here

Which one should you choose?

Skip the spreadsheet if you just need the practical takeaway. Use these rules when deciding between Kimi K2.5 and Claude Sonnet 3.7 (Legacy).

Choose Kimi K2.5 if input tokens dominate your bill

Kimi K2.5 has the lower input rate, which usually matters most for chat, RAG, classification, and long-prompt workflows where prompt volume stays much larger than generated output.

Choose Kimi K2.5 if you generate long answers

Kimi K2.5 is cheaper on output tokens, so it tends to win for report generation, coding assistance, reasoning traces, and any workflow where completions are long.

Choose Kimi K2.5 if context size is the blocker

Kimi K2.5 offers the larger published context window, which is more important than small pricing differences when you need to fit large files, long chats, or multi-document prompts into one request.

Cost comparison for 10K-token workloads

Side-by-side pricing for identical workloads (10,000 total tokens per request) across different distributions.

Scenario	Kimi K2.5	Claude Sonnet 3.7 (Legacy)	Kimi K2.5 cached
Balanced conversation 50% input · 50% output	$0.0180	$0.0900	$0.0155
Input-heavy workflow 80% input · 20% output	$0.0108	$0.0540	$0.0068
Generation heavy 30% input · 70% output	$0.0228	$0.114	$0.0213
Cached system prompt 90% cached input · 10% fresh output	$0.0084	$0.0420	$0.0039

Frequently asked questions

Which is cheaper: Kimi K2.5 or Claude Sonnet 3.7 (Legacy)?

Kimi K2.5 is cheaper for input tokens at $0.60 per 1M tokens compared to $3.00. For output, Kimi K2.5 costs $3.00 per 1M tokens versus $15.00 for Claude Sonnet 3.7 (Legacy).

What is the cost per 1M tokens for Kimi K2.5?

Kimi K2.5 pricing: $0.60 per 1M input tokens and $3.00 per 1M output tokens. Context window: 262,144 tokens.

What is the cost per 1M tokens for Claude Sonnet 3.7 (Legacy)?

Claude Sonnet 3.7 (Legacy) pricing: $3.00 per 1M input tokens and $15.00 per 1M output tokens. Context window: 200,000 tokens.

How much does it cost per 1K tokens?

Per 1K tokens: Kimi K2.5 costs $0.0006 input / $0.0030 output. Claude Sonnet 3.7 (Legacy) costs $0.0030 input / $0.0150 output. This is useful for calculating small-scale usage costs.

Which model supports a larger context window?

Kimi K2.5 offers 262,144 tokens (262K) versus 200K for Claude Sonnet 3.7 (Legacy).

What is the estimated monthly cost for typical usage?

For a typical workload of 10M input + 2M output tokens per month: Kimi K2.5 would cost approximately $12.00, while Claude Sonnet 3.7 (Legacy) would cost $60.00. Kimi K2.5 is more economical for this usage pattern.

Do these models support prompt caching?

Kimi K2.5 supports prompt caching at $0.100 per 1M cached tokens, reducing costs for repeated context by up to 83%. Claude Sonnet 3.7 (Legacy) does not publish cached pricing.

Which model is best for my use case?

Choose Kimi K2.5 for cost-sensitive applications with high input volume. Choose Kimi K2.5 if you need 262K context for long documents or conversations. Consider prompt caching if you have repeated context. Use our token calculator to model your specific usage pattern.