Comparison
Gemini 2.5 Pro vs Kimi K2.7 Code
How Gemini 2.5 Pro and Kimi K2.7 Code compare on the numbers that decide the call - and how to switch between them without touching your code.
| Spec | Gemini 2.5 Pro | Kimi K2.7 Code |
|---|---|---|
| Input price / 1Mlower is cheaper | $1.25 | $0.95 |
| Output price / 1Mlower is cheaper | $10 | $4 |
| Context windowbigger fits more | 1.048576M | 262K |
| Typical speedfaster median | 1.1s | 1.1s |
| Quality score | 92/100 | 89/100 |
| Provider | Moonshot AI |
Which should you pick?
- Kimi K2.7 Code is cheaper on input tokens ($0.95 vs $1.25).
- Gemini 2.5 Pro takes a larger context window (1.048576M tokens).
- Kimi K2.7 Code is usually the faster to answer.
- Gemini 2.5 Pro scores higher on the composite quality benchmark.
You do not have to choose permanently. Name one as your first choice and let Final Router fall back to the other when a provider fails - the request still gets answered, and the log shows which model replied.
Common questions
- Is Gemini 2.5 Pro or Kimi K2.7 Code cheaper?
- Kimi K2.7 Code is cheaper on input tokens - $0.95 vs $1.25 per 1M. Neither is marked up: Final Router bills provider list price.
- Can I switch between Gemini 2.5 Pro and Kimi K2.7 Code without changing my code?
- Yes. Both are called through the same OpenAI-compatible endpoint - change only the model id ("google/gemini-2.5-pro" or "moonshot/kimi-k2.7-code"), or let a routing policy fall back from one to the other automatically.