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Anaconda Desktop is currently available through a limited early access program. Anaconda AI Navigator provides many of the same capabilities and is available to all users.

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Exploring models

Anaconda hosts a of open-source and partner models that you can explore and use to test and develop your applications, accessible from the Model Catalog.
Use the search function to locate models by name.
Models page search box
Models with a lock icon beside their name have been restricted from use by your administrator.

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Model catalog views

The model catalog can be displayed as a tile grid, a table, or as a comparative chart. Use the icons in the upper-right of the Model Catalog page to switch between views.
The Tile view displays a list of models in a grid, listed alphabetically. Each tile displays the model’s name, publisher, model type, a dropdown, and the model’s resource requirements. Select any tile to view the model’s details.
Models page tile view

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Model types and tags

A model’s type reflects its training objective and architecture. Anaconda Platform currently supports the following model types: Tags reflect what a model can do beyond its primary purpose. For example, a Text Generation model might also support code generation. Notable tags include:
  • Embedding: The model can generate vector representations of text for use in semantic search, RAG pipelines, and similarity comparisons.
  • Tool Calling: The model can invoke external tools or APIs to retrieve information or perform actions during inference.
  • Code Generation: The model can produce, complete, or transform source code across one or more programming languages.
  • Guardrail: The model is designed to evaluate or filter content, typically used to enforce safety or policy constraints in AI pipelines.
  • Base Model: The model has not been fine-tuned for a specific task and is intended as a foundation for further training or customization.
  • Instruction Following: The model has been trained to respond reliably to structured instructions or prompts.

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Filtering models

Apply filters to help you find the models that you want to use.
Filters apply to all model views.
To apply a filter:
  1. From the Model Catalog page, select Filter.
  2. Add or adjust a filter to narrow down the list of models.
  3. Repeat as necessary to list only the models you want.

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Model filters

  • Hide restricted models: Filters out models that have been restricted from use by your administrator.
  • Only Show Compatible Models: Filters out models that require more memory than your system’s RAM+VRAM can provide. Enabled by default.
  • Publisher: Filter models by the organization that built them.
  • Quantization: Filter models by the quantization method used to build them.
  • File Size: Adjust the slider to filter models by the amount of disk space they require.
  • RAM: Adjust the slider to filter models by the amount of RAM they require.
  • License: Filter models based on their usage, modification, and distribution terms.
  • Date Published: Filter models based on the date they were published to Desktop. Click Refresh to reset the currently applied date filter.
  • Purpose: Filter models based on their associated model type.
  • Language: Filter models by which spoken languages they can understand.
Select the icon beside any filter to remove it, or select Clear in the All Filters panel to clear all filters at once.
Range filters (File Size and RAM) can be reset by dragging the slider to fill the entire range.
Models page right-hand filters panel

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Viewing model details

Select a model to view its details. From here, you can read a brief description of the model and see important information about it, such as its file size at each quantization level, count, the quality you can expect from the model’s output, how much resource usage can be expected by the model, and its intended purpose (for use in either development or production).
Model details view
Hover over a tooltip to view detailed information about the various aspects of a model.
Select Info URL to visit the Huggingface webpage of the organization that built the model.

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Downloading models

Anaconda provides a variety of LLM models for you to work with, constructed at various levels of quantization. To download a model:
  1. Select Model Catalog from the left-hand navigation.
  2. Locate a model you want to download.
  3. Open the Quantization Method dropdown and select a file quantization level, then select Download to download the model locally.
    Models tile view quantization method dropdown
    Models that show a Start Server or Chat button on their tile indicate that you have downloaded that quantization level.
By default, models are downloaded to the models folder in the Anaconda Desktop directory. To change the download location:
  1. Select your profile icon in the upper-right corner.
  2. Select Settings.
  3. Navigate to the Models section, then select Change Location.
  4. Use the file explorer to select where you’d like to download your models.

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Managing downloads

Manage your downloads using the pause, play, or cancel buttons beside the progress bar at the bottom of the model’s tile.
You can also manage your downloads from the AI Models page.
Downloads automatically pause if you exit the application for any reason.

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Deleting models

To delete models that you have downloaded, navigate to the AI Models page, select Actions beside the model, then select Delete.
Models cannot be deleted while they’re loaded into the API server. On the Model Servers page, select Stop Server to unload a model.