Run DeepSeek v4.1 Flash on your Mac (github.com)

WARP has made significant strides with the release of its embeddable inference engine capable of running advanced AI models directly on consumer hardware, including a 64 GB MacBook Pro. With the goal of executing massive models like Kimi K3—which boasts a staggering 2.78 trillion parameters—WARP leverages a strategic approach of streaming expert models directly from disk while maintaining a shared trunk in RAM to minimize memory overhead. This innovation allows users to achieve speeds of around 0.6 tokens per second for Kimi K3 at full capacity, while DeepSeek-V4.1-Flash and GLM-5.3-Flash models perform at approximately 3.8 and 3.9 tokens per second, respectively. This development is significant for the AI/ML community because it pushes the boundaries of what's possible with local inference on standard consumer devices. Key technical insights include the mechanism of using a bounded expert cache, a lookahead router that predicts future expert needs, and employing unique quantization methods for efficient memory use. Notably, the WARP engine takes advantage of efficient storage strategies, allowing models to execute complex tasks without being constrained by excessive hardware requirements, thus democratizing access to high-performance AI capabilities. These advancements open new possibilities for researchers and developers working with large-scale AI implementations on everyday machines.