gemini-3.8-flash vs kimi-k2.6
| gemini-3.8-flash | kimi-k2.6 | |
|---|---|---|
| Providers | — | — |
| Input $/M | $1.50 | $1.00 |
| Output $/M | $7.50 | $4.15 |
| Output multiplier | ×5.00 | ×4.15 |
| Context window | — | — |
| Intelligence index | 40.9 | 27.0 |
| Coding index | 76.3 | 61.8 |
What the numbers mean
Input pricing is close — 1.50× apart — so the decision should come down to measured quality on your own evaluation set rather than headline cost.
On measured intelligence index the gap is 13.9 points, with gemini-3.8-flash ahead. That is a large enough spread to be visible on multi-step tasks.
Code
from openai import OpenAI
client = OpenAI(base_url="https://starseaapi.com/v1", api_key="sk-...")
# gemini-3.8-flash
client.chat.completions.create(model="gemini-3.8-flash", messages=[{"role":"user","content":"Hi"}])
# kimi-k2.6
client.chat.completions.create(model="kimi-k2.6", messages=[{"role": "user", "content": "Hi"}])