[ICLR-2025-SLLM Spotlight 🔥]MobiLlama : Small Language Model tailored for edge devices
-
Updated
May 10, 2025 - Python
#
mobile-llm
Here are 10 public repositories matching this topic...
Cross-platform on-device AI toolkit
kotlin swift rust ios privacy unity3d voice-assistant ai-games privacy-tools edge-ai unity-ai on-device-ml on-device-ai voice-ai onnx-runtime llm llamacpp ollama mobile-llm
-
Updated
Sep 24, 2026 - Rust
on-mobile-llm is a research-style project that evaluates how well small language models (0.5B–2B parameters) run fully offline on an Android smartphone using GGUF + llama.cpp + Termux. The goal is to measure speed, memory usage, thermals, stability, and output quality across a variety of SLM architectures.
-
Updated
Jan 12, 2026 - Shell
Run LLMs on Snapdragon NPU — including the 'unsupported' 8 Gen 1 (Hexagon v69). Verified at 31 tok/s on OnePlus 10 Pro.
snapdragon qnn edge-ai llm-inference oneplus-10-pro mobile-llm executorch on-device-llm android-llm hexagon-npu qualcomm-ai snapdragon-8-gen-1 samsung-galaxy-s22 hexagon-v69
-
Updated
Jun 15, 2026 - Shell
Your AI. Your phone. No cloud. No subscription. No limits. Run powerful language models directly on your Android device , fully offline, completely private.
-
Updated
May 9, 2026 - TypeScript
Curated resource for mobile teams shipping on-device LLMs — runtime benchmarks, model picks, GDPR-friendly architecture, and real production use cases.
cactus mlx litert privacy-first edge-ai on-device-ai mobile-ai mobile-inference ios-ai llama-cpp local-llm gguf small-language-models mobile-llm mobile-agent agentic-ai ondevice-ai on-device-inference on-device-llm android-llm
-
Updated
Jun 22, 2026
Ship production-ready large language models on Android and iOS devices using battle-tested guidance and technical resources.
cactus mlx litert privacy-first edge-ai on-device-ai mobile-ai mobile-inference ios-ai llama-cpp local-llm gguf small-language-models mobile-llm mobile-agent agentic-ai ondevice-ai on-device-inference on-device-llm android-llm
-
Updated
Sep 24, 2026
Compile Gemma 4 E2B for Snapdragon v69 NPU (8 Gen 1). Pipeline scaffolding from 32-agent research synthesis.
qnn mobile-llm executorch on-device-llm gemma4 gemma-4-e2b snapdragon-8-gen-1 hexagon-v69 snapdragon-npu qualcomm-ai-hub
-
Updated
Jun 28, 2026 - Python
A playground for pushing local AI agents as far as possible on edge/mobile and local devices.
-
Updated
Sep 11, 2026 - Kotlin
Add this topic to your repo
To associate your repository with the mobile-llm topic, visit your repo's landing page and select "manage topics."