Curated GGUF weights bundled with the Atlas iOS app (https://github.com/imwithye/atlas). Each file is a community Q4_K_M quantization re-hosted here so the app can pin a stable URL per model and so users don't depend on third-party uploader availability.

All models are picked to fit comfortably on a modern iPhone (≤ 2 GB on disk, ≤ ~4 GB RAM at inference).

One folder per model family. Files are named <family>-<size>[-it]-<quant>.gguf.

Source quant: ggml-org/gemma-3-1b-it-GGUF Base model: google/gemma-3-1b-it

Source quants: bartowski/Llama-3.2-1B-Instruct-GGUF · bartowski/Llama-3.2-3B-Instruct-GGUF Base models: meta-llama/Llama-3.2-1B-Instruct · meta-llama/Llama-3.2-3B-Instruct

Source quant: bartowski/Qwen2.5-1.5B-Instruct-GGUF Base model: Qwen/Qwen2.5-1.5B-Instruct

Source quant: bartowski/Qwen_Qwen3-1.7B-GGUF Base model: Qwen/Qwen3-1.7B

Source quant: HuggingFaceTB/SmolLM2-1.7B-Instruct-GGUF Base model: HuggingFaceTB/SmolLM2-1.7B-Instruct

All weights are Q4_K_M — 4-bit K-quants with mixed precision for select tensors. A good size/quality tradeoff for mobile inference. Run with llama.cpp or any compatible runtime.

Each file inherits the license of its base model. Check the linked base model page before redistribution. Atlas does not re-license the weights.