From the creator of Redis; run LLM locally with ds4
What happened
The open‑source project ds4, created by antirez (the author of Redis), is a C‑based inference engine for running large language models such as DeepSeek V4, GLM 5 and Qwen 3.8 locally. It supports CPU, Metal on macOS and CUDA on Linux, and can stream model data from SSDs to handle models larger than RAM, saving the KV cache to disk for fast restarts. Benchmarks show a DGX Spark serving a request in 17 seconds, far faster than llama.cpp’s several‑minute startup. The tool includes a CLI, an API server and a coding‑assistant agent that share a single engine and model file.
Why it matters
For developers who need private, on‑premise LLM access, ds4 offers a lightweight, fast alternative to cloud services, reducing latency and data‑privacy concerns. It also makes high‑end models usable on consumer‑grade hardware with enough storage.
Reality check
An automated, sceptical read of the sourceIncremental. The engine adds useful streaming and disk‑cache features but builds on existing concepts and models rather than introducing a fundamentally new technology.
Is this a big deal?
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