Your on-device AI companion. Chat, code, assist, partner & forge — every byte stays on this phone.
⚡ Airplane-mode verified · no network permissions
Interactive prototype — responses are simulated.
DEMO · replies are canned — production runs llama.cpp r4b via JNI, 100% offline
🜲
Ablitrack
Abliterated models · zero telemetry
Choose your persona
Active model
Llama-3.1-8B abliterated · Q4_K_M
4.9 GB · GGUF mmap · KV-cache 512 MB
Quick start
🌌 Space talk
⌨️ Kotlin retry
📅 Plan my week
🎨 Image Forge
‹
💬
Conversationalist
Llama-3.1-8B · CPU · ~11 tok/s
🗑
‹🎨 Image Forge
Text-to-image · on-device · planned v2
🖼️
Generation slot reserved
v2 wires stable-diffusion.cpp behind the same JNI hardware-abstraction layer. Quantized SD-1.5-class model, ~40–90 s per 512×512 image on this class of device.
Prompt
📷 Photoreal
🖋 Anime
🎹 Concept
🧪 Negative prompt
Why it's a placeholder
Runtimestable-diffusion.cpp (planned)
ModelSD-1.5-class · GGUF quantized
Transportsame JNI HAL as chat
StatusUI scaffold in v1
‹📦 Model Manager
Real abliterated GGUF repos from Hugging Face
38.2 GB
Storage free
4
Repos listed
Catalog · hubbartowski / DavidAU
Downloads here are simulated for the prototype. In the production APK each entry streams its GGUF
directly from these Hugging Face repos over a one-time connection, then runs fully offline forever.
‹⚙️ Hardware Abstraction
llama.cpp backend selection & device telemetry
11 t/s
Generation
38 t/s
Prompt eval
39°C
SoC temp
🧠 Inference backend
📱 Detected device
SoCSnapdragon 8 Gen 3
CPU8 cores · NEON · i8mm · dotprod
GPUAdreno 750 · Vulkan 1.3
RAM16 GB LPDDR5X
Thermal gov.SUSTAINED
Battery87% · discharging OK
🧩 llama.cpp session
GGUF mmap4.9 GB mapped
KV cache512 MB · f16
Context8192 tok
Threads4 / 8
Flash attnenabled
Context window
CPU threads
🔒 Privacy ledger
Network sockets0 open
Data sent off device0 bytes
Telemetry processesnone installed
Model weightsapp-private storage
🜲 Ablitrack
v1.0 · offline prototype
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Every feature lives on-device. The back button navigates in-app — there is no cloud to exit to.