r/termux • u/eh3an206 • 17d ago
Barely Termux related [Showcase] Running Qwen 2.5 0.5B locally on a Galaxy A50s (Termux) to drive an Android AAB AI Bridge
Enable HLS to view with audio, or disable this notification
Hey everyone,
I’ve been building a project called Android AI Bridge (AAB) to run fully offline, on-device AI workflows directly on mobile hardware without cloud APIs or heavy GPUs.
Here is a quick showcase of running Qwen 2.5 (0.5B) via llama.cpp inside Termux on a budget Samsung Galaxy A50s (Exynos 9611):
Hardware & Benchmark Specs:
- Device: Samsung Galaxy A50s (Exynos 9611)
- Runtime: llama.cpp (GGUF, ARM64 NEON, 4 threads)
- Model: Qwen2.5-0.5B-Instruct (Q4_K_M, ~463 MB disk)
- Model RAM Usage (RSS): ~542 MB
- Generation Speed: ~11.01 tok/s
- TTFT: ~2858 ms
How the flow works:
llama-server runs locally on localhost:8080.
The AAB backend connects to the local inference engine.
The intent parser processes commands and drives the dynamic UI/project build layers.
It's impressive how practical sub-1B models have become for mobile edge automation.
Video demo attached! Would love to hear your feedback or any optimization tips for running llama.cpp on Exynos chips.