Long documents, read whole.
Give the model the whole thing: a contract bundle, a stack of papers, a codebase, a year of meeting notes. Ask questions across all of it instead of pasting in pieces.
Pre-launch. Accounts are open; the API and checkout open soon.
How it runs.
01
Put it all in.
Up to the model’s full window: 1M tokens on Kimi K3.
02
Ask across it.
Compare clauses, trace a function through the codebase, find what changed between drafts.
03
Ask again.
Every follow-up resends the whole document. On lanes that doesn’t cost more.
Why lanes fit it.
Input is the whole cost.
Reading a million tokens to answer one question is what per-token bills charge most for.
Long context has a lane price.
A request past the default context takes twice its lanes on Solo and Pro, and nothing extra on the others. No surcharge per token.
Keep the conversation going.
Ask as many follow-ups as you like.
Works with what you use.
OpenAI Python
python
import osfrom openai import OpenAI client = OpenAI( base_url="https://api.voidstone.net/v1", api_key=os.environ["VOIDSTONE_API_KEY"],) stream = client.chat.completions.create( model="kimi-k3", messages=[{"role": "user", "content": "Explain this stack trace."}], stream=True,)for chunk in stream: print(chunk.choices[0].delta.content or "", end="")