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Comparison

moby vs Awesome-LLM-Inference

Verdict

Pick moby when moby is primarily Go; Awesome-LLM-Inference is Python; pick Awesome-LLM-Inference when awesome-LLM-Inference is primarily Python; moby is Go.

Markdown twin · moby alternatives · Awesome-LLM-Inference alternatives

GraphCanon updated today

moby logo

moby

moby/moby

★ 72kpushed Jul 10, 2026
vs
Awesome-LLM-Inference logo

Awesome-LLM-Inference

xlite-dev/Awesome-LLM-Inference

★ 5.4kpushed Jun 23, 2026

Trust & integrity

SignalmobyAwesome-LLM-Inference
Maintenance
Very active (1d since push)
As of today · github_public_v1
Active (18d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
No criticals
As of today · osv@v1
No lockfile
As of today · none
moby trust reportAwesome-LLM-Inference trust reportTrust methodology

Tagline

moby
The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems
Awesome-LLM-Inference
📚A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.🎉

Stars

moby
72k
Awesome-LLM-Inference
5.4k

Forks

moby
19k
Awesome-LLM-Inference
421

Open issues

moby
3.8k
Awesome-LLM-Inference
4

Language

moby
Go
Awesome-LLM-Inference
Python

Adopt for

moby
-
Awesome-LLM-Inference
-

Persona

moby
-
Awesome-LLM-Inference
-

Runtime

moby
-
Awesome-LLM-Inference
-

License

moby
Apache-2.0
Awesome-LLM-Inference
GPL-3.0

Last pushed

moby
Jul 10, 2026
Awesome-LLM-Inference
Jun 23, 2026

Categories

moby
Developer Tools, Inference & Serving, LLM Frameworks
Awesome-LLM-Inference
Inference & Serving, LLM Frameworks

Trust and health

Maintenance

moby
Very active (96%)
Awesome-LLM-Inference
Active (82%)

Days since push

moby
1d
Awesome-LLM-Inference
18d

Open issues (now)

moby
3.8k
Awesome-LLM-Inference
4

Security scan

moby
No criticals
Awesome-LLM-Inference
No lockfile

Full report

moby
Trust report
Awesome-LLM-Inference
Trust report

Choose moby if…

  • moby is primarily Go; Awesome-LLM-Inference is Python.
  • License: moby is Apache-2.0, Awesome-LLM-Inference is GPL-3.0.
  • Tags unique to moby: containers, docker, go, golang.
  • Also covers Developer Tools.
  • moby ships Docker support for self-hosted deployment.

When NOT to use moby

  • Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Choose Awesome-LLM-Inference if…

  • Awesome-LLM-Inference is primarily Python; moby is Go.
  • License: Awesome-LLM-Inference is GPL-3.0, moby is Apache-2.0.
  • Tags unique to Awesome-LLM-Inference: awesome-llm, deepseek, deepseek-r1, deepseek-v3.

When NOT to use Awesome-LLM-Inference

  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Explore

moby trust report →Awesome-LLM-Inference trust report →Developer Tools category →Inference & Serving category →LLM Frameworks category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: moby 72k · Awesome-LLM-Inference 5.4k (synced Jul 11, 2026).

Common questions

What is the difference between moby and Awesome-LLM-Inference?
moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. Awesome-LLM-Inference: 📚A curated list of Awesome LLM/VLM Inference Papers with Codes: Flash-Attention, Paged-Attention, WINT8/4, Parallelism, etc.🎉. See the comparison table for live GitHub stats and shared categories.
When should I choose moby over Awesome-LLM-Inference?
Choose moby over Awesome-LLM-Inference when moby is primarily Go; Awesome-LLM-Inference is Python; License: moby is Apache-2.0, Awesome-LLM-Inference is GPL-3.0; Tags unique to moby: containers, docker, go, golang; Also covers Developer Tools; moby ships Docker support for self-hosted deployment.
When should I choose Awesome-LLM-Inference over moby?
Choose Awesome-LLM-Inference over moby when Awesome-LLM-Inference is primarily Python; moby is Go; License: Awesome-LLM-Inference is GPL-3.0, moby is Apache-2.0; Tags unique to Awesome-LLM-Inference: awesome-llm, deepseek, deepseek-r1, deepseek-v3.
When should I avoid moby?
Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
When should I avoid Awesome-LLM-Inference?
Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is moby or Awesome-LLM-Inference more popular on GitHub?
moby has more GitHub stars (71,899 vs 5,383). Stars measure visibility, not whether either tool fits your constraints.
Are moby and Awesome-LLM-Inference open source?
Yes - both are open-source projects on GitHub (moby: Apache-2.0, Awesome-LLM-Inference: GPL-3.0).
Where can I find alternatives to moby or Awesome-LLM-Inference?
GraphCanon lists graph-backed alternatives at moby alternatives and Awesome-LLM-Inference alternatives (moby markdown twin, Awesome-LLM-Inference markdown twin), ranked by typed relationship edges rather than popularity votes.
Is there a machine-readable version of this comparison?
Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
Which is better maintained, moby or Awesome-LLM-Inference?
moby: Very active. Awesome-LLM-Inference: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.
Where are the full trust reports for moby and Awesome-LLM-Inference?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: moby trust report; Awesome-LLM-Inference trust report.