Test Gemma 4 -gpu model files before switching the catalog
Maintainers usually reply within 1 day
Nobody has claimed this yet.
Assessment
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Newbie friendliness
- 55/100
- Issue type
- Feature
- Clarity
- Clearly specified
- Activity status
- Active
- Tech stack
- dart
- Domain
- machine-learning, mobile
Research direction
Start with #216 and the catalog entry in lib/data/repositories/ai_model_repository_impl.dart. On a real phone, compare the generic and -gpu Gemma 4 E2B files on GPU, then force CPU with the -gpu file; repeat for E4B if E2B looks promising. Done means the load, prefill, decode, and memory comparisons support a clear decision about whether to switch, while confirming whether CPU fallback still works.
Written by the indexing model from the issue text.
Description
What
Test whether the special GPU model files for Gemma 4 are better for us, before changing the catalog.
Why
Both Gemma 4 repos on Hugging Face ship two versions of the model:
| Model | What we download today | Also available |
|---|---|---|
| Gemma 4 E2B | gemma-4-E2B-it.litertlm |
gemma-4-E2B-it-gpu.litertlm |
| Gemma 4 E4B | gemma-4-E4B-it.litertlm |
gemma-4-E4B-it-gpu.litertlm |
Now that the app prefers the GPU on Android (#216), the -gpu file might load faster or run faster.
But the model card doesn't explain what's different, so we should not switch blindly.
Risk to check
The -gpu file may be GPU-only. If it is, our CPU fallback would break — phones where the GPU fails would not be able to run Gemma 4 at all. This has to be tested before switching.
How to test (on a real phone)
- Download both files for Gemma 4 E2B.
- Run the same prompt with each, on GPU, and compare from the log:
- load time
- prefill (reading the prompt) time
- decode (writing the answer) speed
- memory use
- Force CPU with the
-gpufile and check it still loads. If it doesn't, we can't use it as the only download. - Repeat for E4B if E2B looks good.
Decide
- Faster and still works on CPU → switch the catalog URL in
lib/data/repositories/ai_model_repository_impl.dart - Faster but GPU-only → keep the generic file (or download per device, which is a bigger change)
- No real difference → keep the generic file and close this
Depends on #216.
- Dominant language
- Dart
- Stars
- 2
- Forks
- 2
- Avg merge
- 1d 35m
- Merged PRs (30d)
- 36
Getting set up
- No Dockerfile or Docker Compose file
- No pull request template
- Read the contributing guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
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