Menu

Run a Local LLM on Android: What RAM Tier You Need and Which Models Actually Work
πŸ“°

Run a Local LLM on Android: What RAM Tier You Need and Which Models Actually Work

DEV CommunityΒ·EngineeredAIΒ·6 months ago
#BCEDaaFg
#localllm#android#llm#model#models
Reading 0:00
15s threshold

TLDR: Modern Android flagships can run 7B parameter models locally. Here's the threshold, the app, and the one setting that matters.

The setup I tested:

ROG Phone 7 Ultimate, Snapdragon 8 Gen 2, 16GB RAM. App: Off Grid. Model: Qwen 3 4B, Q4_K_M quantization. Speed: 15–30 tokens per second. Use case: lightweight workflow triggers without touching cloud tokens.

RAM thresholds

6GB β€” 1B to 3B models. Technically works. Not practically useful for anything beyond autocomplete.

8GB + Snapdragon 8 Gen 2 β€” 3B to 7B models. This is the useful tier.

12GB+ β€” Llama 3.2 7B and Qwen 3 4B without thermal throttle issues.

The app

Off Grid handles NPU routing automatically on supported Snapdragon hardware. Supports Qwen 3, Llama 3.2, Gemma 3, Phi-4, and any GGUF you want to import from local storage. First thing to do after install: go to settings, switch KV cache to q4_0. That's it.…

Continue reading β€” create a free account

Join HashtagPLUS to read full articles, follow hashtags, vote, and join the conversation.