Qwen3 0.6B fails to load after flutter_edge_ai 2.3 / litertlm 1.13 bump
Los mantenedores suelen responder en 1 día
Nadie ha tomado este issue todavía.
Evaluación
- Dificultad
- 4/5
- Tiempo estimado
- 3-5 días
- Aptitud para principiantes
- 18/100
- Tipo de issue
- Error
- Claridad
- Bastante claro
- Estado de actividad
- Activo
- Stack tecnológico
- android, dart
- Área
- machine-learning, mobile
Línea de trabajo
Start with the failing path in the LiteRT-LM client at src/ffi/litert_lm_client.dart (initialize, around line 956) and LiteRtLmEngine.createModel in litert_lm_engine.dart (line 167), then reproduce with integration_test/llm_stability_e2e_test.dart, which is listed in all_tests.dart. The open question is whether Qwen3-0.6B needs re-conversion for LiteRT-LM 0.18 or a different load setting, and the issue still lacks those probe results. Done means either the model loads on the bumped packages or AIModelId.qwen25_05b is gated behind a load check with a fallback to Gemma.
Escrito por el modelo de indexación a partir del texto del issue.
Descripción
Summary
After bumping to flutter_edge_ai 2.3.2 / flutter_edge_ai_litertlm 1.13.2 (LiteRT-LM 0.18.0, see #257), Qwen3 0.6B (Qwen3-0.6B.litertlm) no longer loads on device. The same file loads and answers on our current packages. Gemma 4 E2B is unaffected.
Error
BackendInitException: all FFI backends failed. Last attempted cpu. Attempts:
gpu: Exception: Failed to create engine. Model may be invalid: .../app_flutter/Qwen3-0.6B.litertlm;
cpu: Exception: Failed to create engine. Model may be invalid: .../app_flutter/Qwen3-0.6B.litertlm
#0 LiteRtLmFfiClient.initialize (flutter_edge_ai_litertlm/src/ffi/litert_lm_client.dart:956)
#1 LiteRtLmEngine.createModel (litert_lm_engine.dart:167)
Logged just before: [LiteRtLmFfi] litert_lm_engine_create took 91ms, then [LiteRtLmEngine] cpu backend failed, no candidates are left.
Evidence it is the package, not our code or the file
| Result | |
|---|---|
Old: flutter_gemma 1.8.3 + _litertlm 1.6.3 (native 0.16.0), same phone, same file |
loads, replies (<think> ... ) |
New: flutter_edge_ai 2.3.2 + _litertlm 1.13.2 (native 0.18.0-e) |
Failed to create engine. Model may be invalid on GPU and CPU |
| File on device | 614,236,160 bytes, identical size to the pushed fixture |
Gemma 4 E2B (gemma-4-E2B-it.litertlm) on the new packages |
all cases pass |
Device: vivo 1933, Android 11 (API 30), arm64. The native bundle downloaded and verified its checksum (native-v0.18.0-e), so it is not a corrupt download.
How it was found
New device test integration_test/llm_stability_e2e_test.dart (runs every model fixture). Before it, every baseline and post-bump device test ran on Gemma, so the Qwen regression was invisible.
Impact
Qwen3 0.6B is in our local catalog (AIModelId.qwen25_05b). On the bumped packages it cannot be activated, so anyone who picked it would get no local model.
Open
- Probe in progress: does a different
maxTokens(256 / 1024 / 4096) or an explicit CPU backend load it? Results will be added here. - Whether the file needs re-converting for LiteRT-LM 0.18 (the upstream "Model may be invalid" text suggests a format check). I could not confirm without upstream.
Proposed handling
- Report upstream (
flutter_edge_ai) with the table above. - Until fixed, do not ship the bump with Qwen3 0.6B in the catalog, or gate it behind a load check with a clear message and fall back to Gemma.
- Keep
llm_stability_e2e_testinall_tests.dartso this is caught on every device run.
Related: #257 (the bump), #88 (device tests).
- Lenguaje dominante
- Dart
- Estrellas
- 2
- Forks
- 2
- Merge medio
- 1 d 35 min
- PR fusionados (30 d)
- 36
Preparar el entorno
- Sin Dockerfile ni archivo de Docker Compose
- Sin plantilla de pull request
- Leer la guía de contribución
Primeros pasos
- Lee el issue completo y luego la guía de contribución del proyecto.
- Comenta en el issue que vas a ocuparte — evita que dos personas hagan lo mismo.
- Haz un fork del repositorio y trabaja en una rama.
- Abre un pull request que haga referencia al número del issue.
Más de basictech01/uniun
-
bug good first issue
Dificultad 2/5 1-3 horas Aptitud para principiantes 82/100
basictech01/uniun#300 ·
Los mantenedores suelen responder en 1 día
-
bug good first issue
Dificultad 3/5 1-2 días Aptitud para principiantes 52/100
basictech01/uniun#301 ·
Los mantenedores suelen responder en 1 día
-
enhancement good first issue P2-Medium
Dificultad 5/5 Más de una semana Aptitud para principiantes 25/100
basictech01/uniun#296 ·
Los mantenedores suelen responder en 1 día
-
bug good first issue P2-Medium
Dificultad 4/5 1-2 días Aptitud para principiantes 22/100
basictech01/uniun#293 ·
Los mantenedores suelen responder en 1 día
-
P3-Low
Dificultad 4/5 1-2 días Aptitud para principiantes 30/100
basictech01/uniun#282 · 1 comentario ·
Los mantenedores suelen responder en 1 día
Todos los issues de basictech01/uniun
Issues similares
-
Dificultad 2/5 1-3 horas Aptitud para principiantes 78/100
Los mantenedores suelen responder en 1 día
-
Dificultad 2/5 1-3 horas Aptitud para principiantes 82/100
Los mantenedores suelen responder en 1 día
-
good-first-issue P3
Dificultad 2/5 1-3 horas Aptitud para principiantes 88/100
flutter/dart-intellij-third-party#758 ·
Los mantenedores suelen responder en 1 día
-
Bug: Incorrect location coordinates on logged Sound Meter dataPosiblemente ocupada @Jashan32 la tomó hoy. Abierto
Dificultad 2/5 1-3 horas Aptitud para principiantes 72/100
Los mantenedores suelen responder en 1 día
-
area/archive bug
Dificultad 2/5 1-3 horas Aptitud para principiantes 76/100
DarkFlippers/qUnleashed#374 ·
Los mantenedores suelen responder en 1 día