Community .aimodel bundles of Gemma 4 (E2B, E4B, 12B, 31B) for Apple Core AI on iOS 27 / macOS 27, with recipes and measured speeds.
Daisuke Majima (MLBoy) PRO
mlboydaisuke
AI & ML interests
On-device AI. Core AI model zoo (60+ models) · devicemark iPhone LLM leaderboard · author of "The Art of Core AI" → github.com/john-rocky
Recent Activity
new activity about 7 hours ago
LiquidAI/LFM2.5-8B-A1B:Add an Apple Core AI row to the Inference table new activity about 7 hours ago
LiquidAI/LFM2.5-2.6B:Add an Apple Core AI row to the Inference table new activity about 7 hours ago
nvidia/nemotron-3.5-asr-streaming-0.6b:Add a community Apple Core AI section under "How to Use this Model"Organizations
PyTorch models exported to ExecuTorch .pte for on-device inference — XNNPACK (CPU, portable) and Core ML builds, each parity-checked.
PyTorch models converted to Core ML for on-device inference on iPhone, iPad and Mac.
Community .aimodel bundles of Gemma 4 (E2B, E4B, 12B, 31B) for Apple Core AI on iOS 27 / macOS 27, with recipes and measured speeds.
Models converted to Apple's Core AI format for on-device inference on iPhone, iPad and Mac — LLMs, VLMs, ASR, TTS and a vision zoo.
PyTorch models exported to ExecuTorch .pte for on-device inference — XNNPACK (CPU, portable) and Core ML builds, each parity-checked.
Models I converted to LiteRT and shipped to litert-community: LLMs, VLMs, embeddings, TTS, ASR, and a vision zoo. Measured on-device.
PyTorch models converted to Core ML for on-device inference on iPhone, iPad and Mac.