antirez/ds4
DeepSeek 4 Flash and PRO local inference engine for Metal, CUDA and ROCm observed · 2026-08-28
Health v2 · maintenance only
58/100
- Activity 99
- Release rhythm 35
- Longevity 8
Flags: no_releases young
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 119
- days_rel: n/a
- days_push: 10
- n_releases_24m: 0
Adoption not part of the score
21807 stars · 2017 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
DwarfStar (ds4) is a self-contained native LLM inference engine written in C, optimized for DeepSeek V4 Flash and PRO and GLM 5.2, with support for Metal, CUDA, and ROCm backends. It includes model loading, prompt rendering, tool calls, KV caching, an HTTP server, and a coding agent, plus tools for GGUF quantization and benchmarking.
Use cases
- run DeepSeek V4 Flash locally on a MacBook with Metal
- serve a multi-user LLM server on old CUDA cards with micro batching
- run large models on machines without enough RAM using SSD streaming
- use tensor parallelism across two Macs with RDMA
- run inference on Strix Halo systems with ROCm
- quantize models to GGUF with imatrix and evaluate quality and speed
When to avoid
- you need a general-purpose GGUF runner for arbitrary models
- you prefer a mature multi-model framework like llama.cpp or vLLM
- you are uncomfortable with AI-assisted developed code
Facets
application · maturity active
llm-inference http-server gpu-computing large-language-models artificial-intelligence self-hosted cli metal cuda rocm deepseek gguf local-inference tensor-parallelism ssd-streaming macos linux gpu web-server
1 source
- readme: https://github.com/antirez/ds4 · fetched 2026-08-28 · d5943ebf8f53
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| antirez/ds4 | main | 58 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem