Docs/Models
Choosing a model
Which model should I use for what?
Checked against the code on
There is no upgrade to buy and no plan to pick, so the honest answer is: try two. A switch costs one string on the API and one click in the workspace, and the same question on a second model is the fastest way to learn which one you like.
| Job | Reach for | Because |
|---|---|---|
| Everyday questions, drafts, summaries | gemini-3.7-flash | Fast, cheap, a million tokens of context |
| Careful writing, editing, code review | claude-sonnet-5 | Strong at long context and following instructions |
| An all-rounder with tools in mind | gpt-5.6-sol | The closest match if you are moving OpenAI code |
| Hard reasoning where cost does not matter | claude-fable-5.1 | The most capable model on the catalog today |
| High volume on a budget | deepseek/deepseek-v4.1-flash | Capable reasoning at a fraction of a credit per turn |
| A picture | google/gemini-3.1-flash-image | Fast, cheap, works through chat |
| A short video clip | kling-3.0 or veo3-fast | Smooth motion; the workspace shows the price per shape |
What the numbers mean
- Input rate is what you pay per million tokens you send, including the conversation history you resend each turn. Long conversations cost input, not output.
- Output rate is per million tokens the model writes, including reasoning you never see on thinking models.
- Context is the most the model can hold in one call. Bigger is not better; it is a ceiling.
Cheap experiments
Set max_tokens low while iterating on a prompt. The reservation and the worst case of a runaway reply both shrink with it.