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Choosing a model is a trade between three things: how hard the task is, how quickly you need the answer, and what you are willing to spend on it. Most of what an office asks the agent in a day is routine, and the default handles it well. A smaller share of the work is demanding enough that a stronger model pays for itself by getting it right the first time.
The recommendations on this page are starting points. Models differ in style as well as strength, and the best judge of a draft is the person who will sign it. See Test your choice for a quick way to compare.

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Start with three questions

A status summary that misses a detail costs a minute. A deed with the wrong cadastral reference costs a great deal more. The more a mistake would cost, the stronger the model you should pick. Whichever model you use, you review the agent’s edits as tracked changes before they become part of the document.
One short document is easy for every model. Reconciling a purchase contract against a land registry extract, a mortgage offer and three emails is not. Work that spans many sources or many steps benefits most from a frontier model.
Claude models run on Amazon Bedrock in EU regions. ChatGPT models run on the OpenAI Platform with response storage switched off. If a client or an internal policy requires EU inference, pick a Claude model, or ask an admin to set a model policy for the whole organization.

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Model selection table

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Two ways to settle on a model

Leave Auto on and work normally. Move up only when you see a specific shortfall: a draft that reads flat, a detail missed across documents, or an instruction only half followed.This suits offices that use the agent mostly for intake, filing, status and correspondence, and want predictable spend.
  1. Work on Auto.
  2. When a result falls short, re-run the same request on Sonnet 5 or ChatGPT 5.6 Sol.
  3. If that fixes it, use that model for that kind of task from now on.
  4. Keep Auto for everything else.

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Worked examples

Auto. The agent reads the matter, its linked conversations and recent activity, and drafts a reply for your approval. Nothing here needs deep reasoning, and the answer is reviewed before it is sent.
No choice needed. Populate is a workflow with its own fixed model ladder: a fast model for the bulk steps, a balanced model to identify fields and an advanced model to verify the difficult values. The model picker does not affect it.
Opus 5, or ChatGPT 5.6 Sol if cost matters more. The agent must understand each clause, decide what to change and write replacement language in the right register. Edits arrive as tracked changes, so you accept or reject each one.
ChatGPT 5.6 Terra or Sonnet 5. This is checklist work across a known set of documents: thorough rather than subtle.
ChatGPT 6 Astra or Opus 5. Working out which source is authoritative, why they differ, and what to tell the client is the kind of reasoning frontier models are for.
Auto or ChatGPT 5.6 Terra. Browsing is driven by a separate browser service; the conversation model only has to plan the visit and read the result. See Browser sessions.

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What each step up costs

Casa Conect charges what the provider charges, so the price gaps between models are the providers’ own. As a rough guide, measured against the default model: These multiples sound large, but the base is small. A long drafting conversation on a frontier model usually costs less than a few minutes of a lawyer’s time. See AI credits for list prices and for how to set budgets.
Very long conversations cost more per message, because the model re-reads the history on every turn. When you change subject, start a new conversation. It is cheaper and the agent stays focused.

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Test your choice

You do not need a formal evaluation. Take a task you know well and run it twice.
1

Pick a real task with a known good answer

Use a document you have already reviewed by hand, so you can tell at a glance what the agent gets right and wrong.
2

Run it on two models

Send the same request in two separate conversations, one per model. Use a copy of the document if the task edits it.
3

Compare what matters to you

Look at accuracy first, then completeness, then tone. Check the cost of each conversation under Settings → Access & billing → Usage.
4

Write down the result

If a cheaper model is good enough for this kind of task, tell your team. An admin can also narrow the list under Model policies so the choice is simpler.

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Getting more from any model

The model matters less than the instruction. Before moving up a tier, check that you have given the agent what it needs.
  • Attach or mention the documents you want used rather than describing them.
  • Say what good looks like: who the reader is, the language, the length and the format.
  • Use a skill for work you repeat, so the method is written down once.
  • Add guidance for house style and standing preferences, so you do not repeat them in every message.

Working with the agent

Habits that improve results on every model.

Model policies

Restrict the list for your organization.