sparkrun — Part of the Spark Arena ecosystem

PyPI version License Documentation Spark Arena

One command to rule them all

Launch, manage, and stop LLM inference workloads on one or more NVIDIA DGX Spark systems — no Slurm, no Kubernetes, no fuss.

Documentation · Quick Start · Recipes · Spark Arena

Install

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

# 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 for all commands and options.

Updating

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:

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, 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 is the community hub for DGX Spark recipe benchmarks — browse benchmark results, then run them directly with sparkrun.

Official Recipes

Official Recipes 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 are contributed by the community and hosted on GitHub.

Sponsored by

scitrera.ai

License

Apache License 2.0 — see LICENSE for details.

Anonymous Telemetry

sparkrun sends basic anonymous usage telemetry to https://telemetry.sparkrun.dev by default. Events include a random installation id stored in ~/.config/sparkrun/config.yaml, sparkrun version, OS/version, system architecture, and command-specific metadata such as run runtime/model/parallelism/source/hardware counts, benchmark category/framework/profile/result keys, update version and registry counts, and setup-wizard step choices.

The data allows us to make informed decisions about new features for sparkrun or the greater DGX Spark ecosystem.

Telemetry very specifically does not include personally identifiable information or information that may reveal trade secrets. Telemetry does not include hostnames, usernames, local file paths, tokens, secrets, logs, private HF or local models, or full command arguments. Disable it persistently with sparkrun setup telemetry --disable, re-enable with sparkrun setup telemetry --enable, or opt out for one process with SPARKRUN_NO_TELEMETRY=1.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.3.6)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for dbotwinick from gravatar.com dbotwinick

Credits

Author: scitrera.ai

License expression

Apache-2.0
View SPDX License List

Requires

Python >=3.12

Provides Extra

dev

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sparkrun-0.3.1.tar.gz (1.4 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

sparkrun-0.3.1-py3-none-any.whl (932.0 kB view details)

Uploaded Python 3

File details

Details for the file sparkrun-0.3.1.tar.gz.

File metadata

  • Download URL: sparkrun-0.3.1.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for sparkrun-0.3.1.tar.gz
Algorithm Hash digest
SHA256 929253f1fba6248df91d944a06ff34a364ffe4ec953d1c40c62427fc4f98b0a9
MD5 9bf5512a7f6ff41fd8cbb39cbb15f886
BLAKE2b-256 21ac231eb1cb5e84e823af35209bc9aca1fc998a93d796ae826fc3c5b25dbf53

See more details on using hashes here.

Provenance

The following attestation bundles were made for sparkrun-0.3.1.tar.gz:

Publisher: publish-python.yml on spark-arena/sparkrun

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file sparkrun-0.3.1-py3-none-any.whl.

File metadata

  • Download URL: sparkrun-0.3.1-py3-none-any.whl
  • Upload date:
  • Size: 932.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for sparkrun-0.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 ed5ef43c2f86d21f3b4c08e7330c0b19ed4e19564dce2762215c4c2667b01012
MD5 290cad216716a393b0cdbcb9ebdb2bb3
BLAKE2b-256 370fde30d5889291384922e4541e632a26b9479c2b7480bf9b809ea8b3a25188

See more details on using hashes here.

Provenance

The following attestation bundles were made for sparkrun-0.3.1-py3-none-any.whl:

Publisher: publish-python.yml on spark-arena/sparkrun

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

0.3.6

2 files

0.3.5

2 files

0.3.4

2 files

0.3.3

2 files

0.3.2

2 files

This release

0.3.1 This release

2 files

0.3.0

2 files

0.2.40

2 files

0.2.39

2 files

0.2.38

2 files

0.2.37

2 files

0.2.36

2 files

0.2.35

2 files

0.2.34

2 files

0.2.33

2 files

0.2.32

2 files

0.2.31

2 files

0.2.30

2 files

0.2.29

2 files

0.2.28

2 files

0.2.27

2 files

0.2.26

2 files

0.2.25

2 files

0.2.24

2 files

0.2.23

2 files

0.2.22

2 files

0.2.21

2 files

0.2.20

2 files

0.2.19

2 files

0.2.18

2 files

0.2.17

2 files

0.2.16

2 files

0.2.15

2 files

0.2.14

2 files

0.2.13

2 files

0.2.12

2 files

0.2.11

2 files

0.2.10

2 files

0.2.9

2 files

0.2.8

2 files

0.2.7

2 files

0.2.6

2 files

0.2.5

2 files

0.2.4

2 files

0.2.3

2 files

0.2.2

2 files

0.2.1

2 files

0.2.0

2 files

0.1.14

2 files

0.1.13

2 files

0.1.12

2 files

0.1.11

2 files

0.1.10

2 files

0.1.9

2 files

0.1.8

2 files

0.1.7

2 files

0.1.6

2 files

0.1.5

2 files

0.1.4

2 files

0.1.3

2 files

0.1.2

2 files

0.1.1

2 files

0.1.0

2 files

0.0.23

2 files

0.0.21

2 files

0.0.20

2 files

0.0.19

2 files

0.0.18

2 files

0.0.17

2 files

0.0.16

2 files

0.0.15

2 files

0.0.13

2 files

0.0.12

2 files

0.0.11

2 files

0.0.10

2 files

0.0.9

2 files

0.0.8

2 files

0.0.7

2 files

0.0.6

2 files

0.0.5

2 files

0.0.4

2 files

0.0.3

2 files

0.0.2

2 files

0.0.1

2 files

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page