Bringing AI to the Edge
We focus on deploying AI models directly on consumer devices — making AI faster, private, and freely accessible to everyone.
Integrating finance, diet, mood, and reading data entirely on consumer Apple Silicon, producing emergent cross-domain insights with zero data leakage.
Fused matrix-vector kernels enabling concurrent ANE batch prefill + GPU decode on Apple Silicon for Qwen3.5 models.
Benchmarking CoreML ANE prefill + MLX GPU decode for Qwen3.5 on Apple Silicon, with four inference strategies compared.
Native Swift implementation of Qwen3 TTS 0.6B for real-time, on-device speech synthesis.
Multi-stage compression pipeline for deploying Gemma 3 4B VLM on consumer hardware.
AtomGradient is an independent research group dedicated to making AI run efficiently on edge devices. We believe powerful AI should be private, accessible, and free from cloud dependency. All our research is open-source.
Our research powers EchoStream AI — a product line bringing on-device AI capabilities to real-world applications.