ds4 vs TurboLLM
Local LLM inference projects compared
ds4 and TurboLLM help people run language models on their own hardware. ds4 is a model-specific native inference engine with serving and agent workflows, while TurboLLM manages model downloads, multiple inference engines, tuning, and API access through a web app.
ds4: Run DeepSeek and Other LLMs Locally
ds4, also called DwarfStar, is a native inference engine for selected open-weight language models on Apple Metal, NVIDIA CUDA, and AMD ROCm. It suits users with capable local hardware who want model-specific inference, serving, or coding-agent workflows.
TurboLLM: Run Local Language Models With GPU Tuning
TurboLLM runs local language models through a browser interface and OpenAI- or Anthropic-compatible APIs. It suits developers who want hardware-aware tuning and a choice of inference engines, including community forks.
| ds4 | TurboLLM | |
|---|---|---|
| Language | C | TypeScript |
| License | MIT | — |
| Stars | 23.2k | 278 |
| Forks | 2.2k | 40 |
| Last analyzed | Oct 3, 2026 | Oct 3, 2026 |
Key differences
- ds4 targets selected model families and project-produced GGUF files; TurboLLM supports existing GGUF folders, Hugging Face downloads, and multiple llama-server-compatible engines.
- ds4 supports Apple Metal, NVIDIA CUDA, and supported AMD ROCm hardware; TurboLLM runs on Windows, macOS, and Linux, with CPU fallback when a GPU is unavailable.
- ds4 is written in C and is licensed under MIT; TurboLLM is written in TypeScript and uses FSL-1.1 with a future Apache-2.0 grant.
- ds4 bundles an interactive CLI, HTTP server, and native coding agent; TurboLLM provides a browser UI, compatible APIs, a command-line launcher, and an on-demand model gateway.
- ds4 describes itself as beta quality and warns of possible instability and regressions; TurboLLM marks some capabilities, including remote access and Turbo Link, as experimental.
Choose ds4 if you…
- need a native engine for selected DeepSeek, GLM, or Qwen models on supported hardware.
- want SSD streaming, multi-GPU support, or distributed execution options for supported setups.
- prefer a bundled CLI, HTTP server, or native coding-agent workflow.
Choose TurboLLM if you…
- want a browser interface to download, load, and chat with local models.
- need OpenAI-compatible or Anthropic-compatible APIs for tools such as Claude Code.
- want to benchmark and tune hardware settings or try custom llama-server-compatible engines.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.