WebLLM mobile

WebLLM Not Working on Mobile: Secure Context and WebGPU Checks

Use this when local AI or Device AI features do not start, model loading never finishes, or a mobile browser reports WebGPU or secure-context problems.

WebLLM depends on browser and device capabilities. The same page can work on one phone and fail on another because browser, OS, GPU driver, memory, and model size all matter.

Symptoms

  • The local model button is disabled or never finishes loading.
  • The browser reports that WebGPU is unavailable.
  • The app works on desktop but fails on a phone or tablet.
  • The first model load is very slow, then stops or refreshes.

Likely causes

  • The page is not running in a secure context. Remote pages usually need HTTPS; local testing can work on localhost or 127.0.0.1.
  • The current browser does not expose WebGPU on the device.
  • The device does not have enough memory for the selected model.
  • The model download or cache was interrupted.
  • A browser-specific difference, privacy setting, or OS update changed local AI behavior.

Step-by-step checks

  1. Confirm that the URL is HTTPS, or that you are using localhost or 127.0.0.1 for local testing.
  2. Open DevTools when available and check whether window.isSecureContext is true.
  3. Check whether navigator.gpu exists in the browser.
  4. Try a current Chrome or Chromium-based browser that is known to expose WebGPU on your device.
  5. Try a smaller model or a shorter prompt if memory pressure appears during loading.
  6. Wait through the first model download when progress is still moving; first load can take longer than later cached loads.
  7. If WebLLM still cannot run, return to normal generation or another fallback path instead of forcing unsafe browser changes.

Fixes and fallback options

  • Use HTTPS for public pages and a trusted local URL for local development.
  • Switch browser only through normal installation channels and avoid unofficial APKs or risky extensions.
  • Reduce model size, close memory-heavy tabs, and retry after the browser has released memory.
  • Clear the app cache only when the model cache appears corrupted or stuck.
  • Use Gemini or manual card drafting when local inference is not available on the current device.

Do not disable security warnings, install unknown browser builds, or bypass device protections just to make WebLLM run.

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