What this error means
AI Model Not Found: Model name is not valid block is a Cursor failure pattern reported for developers trying to fix cursor ide model loading error caused by broken auto-mode model mapping in version 2.4.7+; ghost models fail to load. Based on the imported evidence, treat this as a tool-specific troubleshooting page rather than a generic API error.
Why this happens
dredyson.com detailed guide documents specific error 'AI Model Not Found - Model name is not valid block' triggered by Cursor 2.4.7+ Auto Mode attempting to load non-existent models from broken autoModels.json config. Affects paying Cursor subscription users unable to use AI coding features. DEBUG logs show ModelLoader attempting to load 'block-v2-32k' which doesn't exist in registry. Category: Cursor per mapping rules. Not a duplicate of existing 'model not available' — this is a distinct config corruption variant.
Common causes
- dredyson.com detailed guide documents specific error 'AI Model Not Found - Model name is not valid block' triggered by Cursor 2.4.7+ Auto Mode attempting to load non-existent models from broken autoModels.json config. Affects paying Cursor subscription users unable to use AI coding features. DEBUG logs show ModelLoader attempting to load 'block-v2-32k' which doesn't exist in registry. Category: Cursor per mapping rules. Not a duplicate of existing 'model not available' — this is a distinct config corruption variant.
Quick fixes
- Confirm the exact error signature matches
AI Model Not Found: Model name is not valid block. - Check the Cursor account, local tool state, and provider configuration involved in the failing workflow.
- Compare the failing environment with a known working setup, then change one configuration value at a time.
Platform/tool-specific checks
- Verify the command, editor, extension, or API client that produced the error.
- Compare local settings with CI, deployment, or editor-level settings when the error appears in only one environment.
- Avoid deleting credentials, local model data, or project settings until the failing scope is clear.
Step-by-step troubleshooting
- Capture the exact error message and the command, editor action, or request that triggered it.
- Check whether the failure is account/auth, quota/rate, model/provider, local runtime, or deployment configuration.
- Review the source evidence below and compare it with your environment.
- Apply one change at a time and rerun the smallest failing action.
- Keep the working fix documented for the team or deployment environment.
How to prevent it
- Keep provider/tool configuration documented.
- Record non-secret diagnostics such as tool version, provider name, model name, and command path.
- Add a lightweight check before CI or production workflows depend on the tool.