Alternatives to Roofline AI

ExecuTorch is PyTorch's official solution for deploying AI models on mobile, embedded, and edge devices. It features a 50KB base runtime, 12+ hardware backends including Apple CoreML, Qualcomm QNN, ARM, and Vulkan, and native PyTorch export without format conversions. Powers Meta's on-device AI across Instagram, WhatsApp, Quest 3, and Ray-Ban Smart Glasses, supporting LLMs, vision, speech, and multimodal models.

ONNX Runtime is Microsoft's open-source inference engine for machine learning models in ONNX format. It delivers cross-platform acceleration via execution providers for NVIDIA CUDA, TensorRT, DirectML, CoreML, OpenVINO, and more. Supports training acceleration, quantization, and GenAI workloads. Used in production across Windows, Azure, Office 365, and thousands of applications with pip-installable Python and native C++/C#/Java APIs.

Cactus is a YC-backed low-latency AI engine for mobile and wearable devices that runs LLMs, transcription, embedding, and TTS models locally. It achieves 16-20 tok/sec on older devices and 70+ tok/sec on flagships with ARM SIMD kernels optimized for Snapdragon, Apple, and MediaTek processors. Supports Qwen, Gemma, Llama, DeepSeek with Flutter, React Native, and Kotlin SDKs.

MNN is a lightweight, high-performance deep learning inference engine developed by Alibaba and battle-tested across 30+ Alibaba apps including Taobao, DingTalk, and Youku. It supports TensorFlow, ONNX, PyTorch, and Caffe models with optimized backends for CPU, GPU, and NPU on mobile and edge devices. MNN includes on-device LLM inference, an OpenCV-like image processing library, and Python bindings for rapid prototyping. Apache 2.0 licensed with 15K+ stars.