Quick Answer
The top Android apps for running LLMs locally are MLC Chat, Pocketpal, and Termux with Ollama. MLC Chat is the easiest for beginners. All run fully offline.
Updated: 2026-05
Key Takeaways
As of May 2026, there are three practical ways to run a local LLM on Android: MLC Chat (Machine Learning Compilation), Pocketpal AI, and Termux with Ollama. All three run 100% offline after initial model download — no API key or internet connection required.
MLC Chat uses the MLC-LLM compilation framework to pre-optimize model weights for mobile hardware. You download it from Google Play, select a supported model (Llama 3, Gemma, Phi), and the model downloads and runs directly on the device. Setup takes under 10 minutes.
Pocketpal AI is built by the Hugging Face community and supports loading GGUF model files directly from Hugging Face. This means you can run any GGUF-compatible model, not just a prebuilt list. The tradeoff is a slightly more complex setup requiring manual model selection and download.
| App | Setup Effort | Model Flexibility |
|---|---|---|
| MLC Chat | Easy (Play Store) | Prebuilt models only |
| Pocketpal | Medium | GGUF from Hugging Face |
| Termux + Ollama | Advanced (CLI) | Full Ollama library |
Start with MLC Chat if this is your first Android LLM setup — it has the fastest time to first token and the least configuration. Pocketpal is the upgrade path for users who want to swap models frequently. Termux + Ollama is for developers who already know Ollama and want the exact same CLI workflow on mobile.
A flagship Android phone with 8+ GB RAM handles a 2–3B model at 4–8 tok/s on CPU. Mid-range phones from 2023–2024 are slower (1–3 tok/s) — usable for batch tasks, frustrating for live chat. Do not attempt 7B models on any device with less than 8 GB RAM.
Termux + Ollama is the most powerful option but has the steepest setup curve. You install Termux from F-Droid, then run pkg install ollama inside the terminal. Once installed, all standard Ollama commands work including ollama pull and ollama run. This approach is best for developers who already use Ollama on desktop.
Battery drain matters at the 7B tier and above. A 30-minute chat session with Llama 3 8B Q4 on a flagship phone uses 8–12% battery on average. For frequent use, plug in or stick to 2–3B models like Phi-3 Mini and Gemma 2B that draw less power.
For a full guide to running LLMs on Android including hardware requirements and model recommendations, see the best local LLM apps for Android guide.
pkg update && pkg install ollama. Then use standard Ollama commands: ollama pull llama3 and ollama run llama3. Your device needs 8+ GB RAM for reliable operation.