# Cherry Studio backup versus archive: what is restored?

Separate Cherry Studio backups from its Archive, compare full and Lite content, and verify restore dependencies before relying on a local data recovery plan.

Author: Retrivium team
Updated: 2026-11-03
Canonical URL: https://retrivium.ai/journal/cherry-studio-backup-archive-local-data/
Language: en

Cherry Studio's Archive and backup features solve different recovery problems. Archive provides a place to restore recently removed items inside the application. A backup preserves an application snapshot for a separate recovery or transfer procedure. Neither should be assumed to restore every external model service that the assistant depends on.

## Identify what needs recovery

Use Archive when the question is whether a recently removed item remains recoverable. Use a backup plan when preparing for loss of the application data store or moving to another machine. These scenarios differ in what remains available after the problem occurs.

The [Files guide](https://www.cherryai.com/docs/en/cherrystudio/preview/files/) places Archive under Settings and documents restoration plus permanent deletion. Its automatic cleanup interval limits the recovery window. Check the installed configuration rather than treating an archived item as an indefinite spare copy of an important attachment.

## Compare full and Lite backup scope

The [Data Settings guide](https://www.cherryai.com/docs/en/pre-basic/data-settings/) distinguishes full backups from Lite backups. The full scope includes conversations, assistant configuration and data such as attachments and knowledge-base content. Lite skips categories of data files while preserving a smaller history-and-settings package.

Choose a sample workflow containing a conversation, a file attachment and a knowledge item. Record which artifacts the chosen backup mode should preserve. A backup file's existence and small size do not establish that the omitted file categories can be reconstructed later.

## Include provider settings in the inventory

The data guide documents provider configuration and API keys among backed-up information. Treat the artifact according to its actual contents rather than describing every local backup as harmless text. Keep its storage and access consistent with the user's existing data policy.

The [model service configuration guide](https://www.cherryai.com/docs/en/pre-basic/providers/) describes connections that remain separate dependencies. Restoring a saved provider entry does not start an external local runtime or renew an account's access. Verify the target machine can reach the intended model and identify any settings requiring adjustment.

## Test restoration with representative data

Use a controlled test installation or a documented non-destructive recovery procedure. Do not clear a working data store merely to find out whether a backup is complete. First retain the current state and understand the selected version's restore behavior.

After restoration, open the sample conversation and its attachment, inspect the assistant definition and test the expected knowledge workflow. Then make a bounded model request. These checks distinguish preserved application records from reachable external services and from usable underlying files.

## Keep cleanup separate from routine repair

Archive removal, cache cleanup and application reset have different consequences. The documentation explicitly describes permanent deletion and reset as irreversible operations. They should not be hidden inside a generic recommendation to refresh the application when a model connection fails.

Keep a recovery record naming the app version, backup mode, storage location and verified artifacts. Record what was intentionally omitted and how those dependencies are provisioned. A useful backup decision states which loss it can recover from; it does not confuse an Archive entry, a Lite snapshot and a complete reconstruction of the whole AI workstation.

## Related reading

[llama.cpp server: a local API from a GGUF model](/journal/llama-cpp-server-launch/), [VRAM for LLMs: why model size is only part of the calculation](/journal/vram-and-models/).