Choose the right AI model

Use Auto for mixed requests. For a recurring job, compare a faster model with a more capable one, then keep the option that meets your quality, speed, and cost needs.

Which option should I choose?

Start with the option that matches how you use the agent.

Option	Use it when
Auto	Requests vary in difficulty. Gumloop chooses a model for each message.
Balanced	You want a balanced starting point for everyday work.
Smartest	Difficult reasoning or complex execution makes capability your priority.
A specific model	You want to compare models or use one that passes your tests for a recurring task.

Balanced and Smartest can change over time. Enterprise organizations can customize presets, so their underlying models and settings may differ from Gumloop’s defaults. See AI model governance & configuration.

What are some practical model examples?

Use these as starting candidates, not fixed assignments. Test the actual job rather than choosing by provider name.

Example request	Models to try	What to check
“Extract the customer name, order number, and issue from these support emails.”	GPT-6 Luna or Gemini 3.8 Flash	Accurate fields, missing information, and consistent formatting.
“Find overdue accounts in the CRM and draft a follow-up for each.”	Claude 5.5 Sonnet or Grok 4.7	Correct records, tool arguments, and complete drafts.
“Compare these conflicting reports and recommend a plan with citations.”	GPT-6 Astra or Claude 5.5 Opus	Evidence quality, contradictions, and whether the recommendation follows from the sources.
“Turn this product brief into a polished presentation.”	Claude 5.5 Opus or GPT-6.1 Sol	Structure, visual quality, factual accuracy, and completeness.

For images or screenshots, choose a model with Vision. For long documents, check Context. A larger input capacity isn’t proof of better reasoning. Skills use the agent’s model, not a separate one. Choose for the work the skill requires: formatting supplied text is different from investigating a complex problem.

What criteria does Auto use?

Auto aims to choose a lower-cost model that can handle your request. It considers task difficulty, the tools needed, your instructions, and whether sources or tests can check the answer. Sending messages, changing external data, and delegating to other agents require more capable tiers. Auto can switch to a stronger tier mid-run and shows which model it used. Organization restrictions still apply. See AI Models for details.

How do I select a model?

Open your agent’s Agent tab, then use the Model dropdown.

Open the model picker

Choose a preset, search by model name, or browse by provider.

Check the model card

Hover a model to compare Cost, Speed, Intelligence, Context, Tool Calling, and Vision. Ratings help shortlist candidates; your task results decide the winner.

Select and save

Select your model, then choose Save to apply the agent configuration.

When should I use Fast or Ultrafast?

Use Standard to minimize token costs. Choose Fast or Ultrafast when faster responses justify a higher token rate. Speed is separate from reasoning effort. In the agent’s right-hand configuration panel, open the model dropdown in the Agent tab, then select Speed. GPT-6 Astra and GPT-6.1 Sol offer Standard, Fast, and Ultrafast. GPT-6 Sol and GPT-6 Luna offer Standard and Fast. Other models show only their supported modes. See Credits for speed-mode pricing.

How do I know which model is the best fit?

Test candidates on the same prompts, instructions, skills, tools, and source material.

Define a pass: required facts, format, actions, and acceptable completion time.
Try realistic cases: ordinary requests, difficult inputs, and previous failures. Use fresh chats and repeat important cases.
Compare finished results: correctness, tool actions, time, and corrections needed. Select the chat-header credit count for the full cost breakdown.
Keep the option that passes: improve instructions or try a stronger model if it fails. Re-test after material changes.

Test writes with non-production records or approval safeguards. For consequential work, establish a reliable result first, then optimize cost.

FAQ

Why didn't a stronger model fix the result?

Check source data, connector access, instructions, and skills first. More capability cannot grant missing access. Make the success criteria clear before comparing models.

Why can't I select a model?

Your organization or custom role may restrict it. Auto does not bypass those restrictions. A model marked Restricted by Admin requires the appropriate access.

AI models

Model capabilities, Auto routing, and provider keys

Credits

Understand the cost of completed tasks

​Which option should I choose?

​What are some practical model examples?

​What criteria does Auto use?

​How do I select a model?

​When should I use Fast or Ultrafast?

​How do I know which model is the best fit?

​FAQ

​Related