BaseRT - Apple M5 Optimized.

BaseRT - Apple M5 Optimized

BaseRT is a high-performance inference runtime engineered specifically for Apple Silicon, delivering industry-leading speed for local AI model execution. With up to 33% faster decode speeds than MLX and llama.cpp, and up to 6.4x faster prefill performance, BaseRT enables developers to run large language models entirely on-device without compromising throughput or latency.

Product Highlights

• Apple M5 Native Optimization: Built from the ground up to leverage the full compute potential of Apple Silicon architecture, including unified memory and neural engine capabilities.
• Superior Inference Speed: Achieves 531 tokens/sec on Qwen3 0.6B decode tasks—33% faster than competing runtimes—with consistent gains across model sizes and quantization levels.
• Privacy-First Local Execution: Run coding agents and AI workflows completely offline, eliminating API dependencies and ensuring sensitive data never leaves your device.
• Seamless Integration: Simple one-line installation and native compatibility with popular agent frameworks, enabling production-ready deployment in minutes.
• Broad Model Support: Optimized for leading open-source architectures including Gemma 4, Llama 3.2, and Qwen3 with multiple quantization options.

Use Cases

• Local Coding Agents: Power intelligent development assistants that run entirely on your machine—no cloud latency, no token costs, complete code privacy.
• On-Device AI Research: Experiment with and benchmark large language models using maximum hardware utilization without external infrastructure.
• Enterprise Edge Deployment: Deploy secure AI capabilities in environments with strict data residency requirements or limited network connectivity.
• High-Frequency Inference Applications: Build responsive applications requiring sustained token generation speeds for real-time user interactions.

Target Audience

BaseRT is designed for AI engineers, ML researchers, and privacy-conscious developers who demand maximum inference performance on Apple Silicon hardware. It serves teams building production-grade on-device AI systems where speed, security, and cost efficiency are non-negotiable requirements.