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• New LiteRT-LM engine: run .litertlm models, with image and audio input • Updated llama.cpp engine: faster on modern CPUs, optional GPU acceleration on Snapdragon devices • Continuing a saved dialog is much faster • RAG: choose the embedding model (built-in Gecko or a downloaded GGUF) • Model downloads resume after a dropped connection • Many bug fixes and stability improvements
Launch AI LLM neural networks as DeepSeek, Gemma, Qwen local on smartphone
You can download and run AI LLM neural networks such as Google Gemma, DeepSeek, Llama, Qwen and many others on your smartphone. There are quite a lot of AI applications now, but the key difference of this one is that the models do not work in the cloud on servers, but directly on the smartphone from the model file, using the processor and video card of the smartphone. To run, you do not need the Internet, a paid subscription, it is enough to have a smartphone with 6+ GB of RAM and a more or less modern processor. The application works with the HuggingFace repository this is the largest repository with millions of OpenSource models, of which thousands are large language models, or LLM. The application can open the most common model format .gguf using the LLama.cpp engine, as well as the format from Google for the MediaPipe engine - .task and .tflite (versions for MediaPipe are in the Google repository). For some models, such as Gemma 3n (OpenSource version of Gemini) via the MediaPipe engine, image processing is supported. This application is made primarily for AI enthusiasts, as well as for those who cannot use cloud models like ChatGPT or Gemini due to possible data leakage, as well as for people who do not have constant access to the Internet.
past month, based on 1 day
Downloads
Low confidence616
From install count ÷ months since release
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$0
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In-app + ads
Google Play only. Downloads from daily Top free ranks (or the store's install count); in-app revenue from Top grossing ranks, calibrated on AppTweak's US estimates, or else from downloads; ads from public ad benchmarks. Not reported figures.