Model Selection

Choose which AI model powers your Tabnine CLI interactions.

Opening the Model Dialog

/model

This opens an interactive dialog showing available models.

Available Models

Tabnine CLI uses the same models described on the AI Models page.

Changing Models

Via /model Command

1

Open the model dialog

Run:

/model

This opens the interactive model selection dialog.

2

Navigate

Use the arrow keys or J / K to move through available models.

3

Select

Press Enter to select the highlighted model.

4

Immediate effect

Model changes take effect immediately after selection.

Via /model set (Non-Interactive)

You can also change the model without opening the dialog:

/model set <model-name>

This sets the model for the current session only. To persist the change across sessions, add the --persist flag:

/model set <model-name> --persist

Via --model Flag

Specify the model when launching Tabnine CLI:

tabnine --model <model-name>

The -m short form also works:

tabnine -m <model-name>

Via Environment Variable

Set the TABNINE_MODEL environment variable before launching:

TABNINE_MODEL=<model-name> tabnine

Model Selection Precedence

When multiple sources specify a model, the following precedence applies (highest to lowest):

1. --model command-line flag (or -m)

2. TABNINE_MODEL environment variable

3. model.name in settings.json

4. Default model from Tabnine service

Model Information

View current session statistics (including token usage):

/stats

View current model and context usage in the footer (shown if enabled in settings).

Token Limits

Tabnine CLI automatically manages token limits based on the selected model.

Fallback Behavior

If your selected model is unavailable, Tabnine CLI may:

1. Prompt you to select another model

2. Automatically fall back to a default model (depending on settings)

Model Persistence

Your model selection is saved and persists across sessions when using:

• /model set <model-name> --persist — writes model.name to settings.json

• The interactive /model dialog — persists your selection automatically

Persistent selections are stored in .tabnine/agent/settings.json.

Fast Model Configuration

You can configure a lightweight model to handle background CLI tasks, reducing latency for operations the user never directly sees. To configure a fast model, add "fastModel": "<model-name>" to your settings.json or use the /model fast slash command in the CLI.

The following tasks are routed to the fast model when one is configured:

• Session summary

• Shell output summary

• Tool output summary

• Edit corrector

• Fast ack helper

• Loop detection (primary pass)

• LLM edit fixer

Loop detection double-check and next-speaker checker remain on the main model, as they require higher-confidence reasoning. When no fast model is configured, all tasks use the main model. The fast model setting is provider-agnostic and works with any model the backend supports.