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sparkrun - launch, manage, and stop LLM inference workloads on NVIDIA DGX Spark systems
| Date | Stars |
|---|---|
| 2026-07-24 | 404 |
| 2026-07-25 | 409 |
| 2026-07-28 | 414 |
| 2026-07-30 | 414 |
| 2026-07-31 | 415 |
| 2026-08-06 | 415 |
Today
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This week
+1 stars this week
This month
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Momentum
16.0
growth rate 0.24%/day
<p align="center"> <img src="assets/sparkrun-banner.svg" alt="sparkrun — Part of the Spark Arena ecosystem" width="480" /> </p> <p align="center"> <a href="https://pypi.org/project/sparkrun/"><img src="https://img.shields.io/pypi/v/sparkrun?color=76b900" alt="PyPI version" /></a> <a href="https://github.com/spark-arena/sparkrun/blob/main/LICENSE"><img src="https://img.shields.io/github/license/spark-arena/sparkrun" alt="License" /></a> <a href="https://sparkrun.dev"><img src="https://img.shields.io/badge/docs-sparkrun.dev-1e40af" alt="Documentation" /></a> <a href="https://spark-arena.com"><img src="https://img.shields.io/badge/Spark_Arena-community-76b900" alt="Spark Arena" /></a> </p> <h3 align="center">One command to rule them all</h3> <p align="center"> Launch, manage, and stop LLM inference workloads on one or more NVIDIA DGX Spark systems — no Slurm, no Kubernetes, no fuss. </p> <p align="center"> <a href="https://sparkrun.dev">Documentation</a> · <a href="https://sparkrun.dev/getting-started/quick-start/">Quick Start</a> · <a href="https://sparkrun.dev/recipes/overview/">Recipes</a> · <a href="https://spark-arena.com">Spark Arena</a> </p> --- ## Install ```bash uvx sparkrun setup ``` One command — installs sparkrun, then launches the guided setup wizard to create a cluster, configure SSH mesh, detect ConnectX-7 NICs, set up sudoers, and enable earlyoom. ## Quick Start ```bash # Run an inference workload sparkrun run qwen3-1.7b-vllm # Multi-node tensor parallelism (TP maps to node count on DGX Spark) sparkrun run qwen3-1.7b-vllm --tp 2 # Re-attach to logs, stop a workload, check status sparkrun logs qwen3-1.7b-vllm sparkrun stop qwen3-1.7b-vllm sparkrun status ``` Ctrl+C detaches from logs — it never kills your inference job. Your model keeps serving. See the [full CLI reference](https://sparkrun.dev/cli/overview/) for all commands and options. ## Updating ```bash sparkrun update ``` Upgrades sparkrun (when installed via `uv tool`) and refreshes recipe registries. ### Update channels (advanced) Opt into preview builds installed from git instead of PyPI: ```bash sparkrun update --stable # PyPI stable release (default) sparkrun update --beta # develop branch preview sparkrun update --alpha # develop-next branch (bleeding edge) sparkrun update --yolo # alias for --alpha ``` `sparkrun update` with no flag stays on your current channel; a channel flag switches and is remembered for future updates. The same flags work with `sparkrun setup install` and `sparkrun setup update`. Stable prints a plain version (`0.2.40`); beta/alpha add a channel suffix and commit (`0.3.0-alpha+g1a2b3c4`). Switching from a preview channel back to `--stable` may downgrade. ## Highlights - **Multi-runtime** — vLLM, SGLang, llama.cpp out of the box - **Multi-node tensor parallelism** — `--tp 2` = 2 hosts, automatic InfiniBand/RDMA detection - **VRAM estimation** — know if your model fits before you launch (`sparkrun show <recipe>`) - **Git-based recipe registries** — we publish official recipes, community recipes, and benchmarked recipes via [Spark Arena](https://spark-arena.com), plus you can add your own registries. - **Guided setup wizard** — cluster creation, SSH mesh, CX7 auto-detection, sudoers, earlyoom - **Model & container distribution** — syncs models and images to cluster nodes over SSH automatically ## Spark Arena [Spark Arena](https://spark-arena.com) is the community hub for DGX Spark recipe benchmarks — browse benchmark results, then run them directly with sparkrun. ## Official Recipes [Official Recipes](https://github.com/spark-arena/recipe-registry) are maintained by the Spark Arena team and hosted on GitHub. They are tested and optimized for NVIDIA DGX Spark systems. ## Community Recipes [Community Recipes](https://github.com/spark-arena/community-recipe-registry) are contributed by the community and hosted on GitHub. ## Sponsored by <a href="https://
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:952979e3915657fb, topic:inference, topic:llama-cpp, topic:vllm