@VincentLogic: Discovered an amazing open-source project! Redis creator antirez made a splash! ds4 — DeepSeek V4 Flash local inference engine, optimized for Mac Metal, topping GitHub charts for days! And here's the killer part: 128GB…

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Summary

Redis creator antirez released an open-source project called ds4, a DeepSeek V4 Flash local inference engine optimized for Mac Metal, featuring disk KV caching, ultra-long context, and excellent performance.

Discovered an amazing open-source project! Redis creator antirez made a splash! ds4 — DeepSeek V4 Flash local inference engine, optimized for Mac Metal, topping GitHub charts for days! And here's the killer part: A 128GB MacBook Pro M3 Max can run the full DeepSeek V4 at 26 tokens/s generation speed, 58 t/s prefill, supporting 1 million token ultra-long context! The core technology is incredibly hardcore: ✦ Disk KV cache: Uses SSD as VRAM, breaking memory limits ✦ Written in pure C: Extreme performance optimization ✦ Compatible with OpenAI API: Seamless integration with existing Agent tools ✦ Highly compressed KV cache: Memory footprint is extremely stable Even with a 1 million token context, inference is smooth and the memory footprint is rock stable. Mac users who want to experience the pinnacle of local AI must give this a try! Project link in the comments.
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From the creator of Redis; run LLM locally with ds4

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Redis creator antirez released ds4 (DwarfStar 4), a narrow C-based local inference engine for high-memory Mac, CUDA and ROCm machines, supporting DeepSeek V4/V4.1, GLM 5.x and Qwen3.8 Flash Next with asymmetric 2-bit quantization, SSD-backed KV cache, and CLI/server/agent interfaces under an MIT license.

DeepSeek v4.1 Flash 1017 for Dwarfstar (ds4)

Reddit r/LocalLLaMA

nazeshinjite 发布了 DeepSeek V4.1 Flash 1017 的 3.91bpw GGUF 量化版本，面向 antirez 的 DwarfStar (ds4) 推理引擎，采用 SSD 流式加载，可在 128GB Mac 上以最高 20tps 解码。

@PandaTalk8: These test results are stunning. The original poster tested the DS4 inference engine written in C by @antirez, and local deployment seems incredibly fast. The good news is that only 128GB of RAM is needed to run a local model equivalent to GPT-4o. The bad news is that you need a MacBook Pro with 128GB of RAM.

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This article reports on tests of the DS4 inference engine written in C by @antirez, noting its impressive speed when running a GPT-4o-equivalent model on a MacBook Pro with 128GB of RAM.