DeepSeek v4.1 Flash (518GB, 4-bit) on a 128GB MacBook: 2.7x prefill, 17 tok/s (github.com)

DeepSeek has released version 4.1 Flash, leveraging a 518GB model optimized for use on a 128GB MacBook, achieving impressive performance metrics in token processing. The new architecture allows for a 2.7x increase in prompt processing speed by intelligently managing reads from mixed storage setups and reducing unnecessary data pulls. This means the model effectively handles a 512-token input by routing to only 187 of its 384 experts per layer, significantly streamlining the read process and improving efficiency, as each read is split across multiple devices based on their performance. This development is particularly significant for the AI/ML community as it showcases how performance gains can be achieved without the need for bulky hardware, potentially democratizing access to advanced AI capabilities on consumer-grade devices. The key technical implications include enhanced read latency—averaging 5.2 GB/s—where adding additional drives improves performance by reducing the time to access data rather than merely increasing throughput. This innovation opens new avenues for running large-scale models in resource-constrained environments, suggesting practical applications in edge computing and personal AI projects.