Computing Life · Share · YageMay 22, 2026, 08:00 UTC+8

How to Run DeepSeek V4 Flash Locally on Mac: DS4 Engine Explained

如何在 Mac 上本地运行 DeepSeek V4 Flash：DS4 引擎深度解读

DS4 provides a macOS local runtime path for DeepSeek V4 Flash; the post only discloses three mechanisms—multi-agent integration, KV cache disk persistence, and activation steering—and does not disclose performance numbers, hardware requirements, or pricing.

Why it matters: HKR-H/K/R all pass, but the body only names DS4 mechanisms and omits performance, model size, Mac support, and reproducible tests; this fits the featured threshold for a local-inference tutorial.

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DS4 pushes local inference past the hobby-demo line into agent runtime territory. DeepSeek V4 Flash is 284B total parameters, 13B active, and a 1M-token context model; the article says a 96GB-plus Mac can run it. DS4 then adapts it to Claude Code, Codex, and OpenAI chat completions instead of asking users to change tools.

The hook is KV cache as durable state. At 65K context the cache is about 926MB, and the article extrapolates 1M tokens to 13.4GB versus roughly 180GB for a standard transformer. DS4 writes cache files with SHA1 prefixes, token IDs, and graph state, then preserves the original DSML tool-call text across JSON agent hops. I don’t buy the “general Mac inference engine” framing here. This smells like a sharp single-model blade for V4 Flash, far from llama.cpp’s broad-runner path.

Source: Computing Life · Share · Yage · yage.ai
Published: May 22, 2026, 08:00 UTC+8 · May 22, 2026