Home/Compare/airllm vs anubis-oss

Comparison

airllm vs anubis-oss

Verdict

Pick airllm if airLLM is a notable framework designed specifically for running large language models on low-resource hardware, such as a single 4GB GPU; pick anubis-oss if anubis-oss, specifically tailored for Apple Silicon devices using Swift, is distinguished by its focus on local large language model evaluation and testing within the macOS environment.

Markdown twin · airllm alternatives · anubis-oss alternatives

GraphCanon updated 1w

airllm logo

airllm

lyogavin/airllm

24kpushed Jul 23, 2026
vs
anubis-oss logo

anubis-oss

uncSoft/anubis-oss

198pushed Jun 18, 2026

Trust & integrity

Signalairllmanubis-oss
Maintenance
Very active (5d since push)
As of 3w · github_public_v1
Steady (56d since push)
As of 1w · github_public_v1
Provenance
Not a fork · Personal account
As of 3w · github_public_v1
Not a fork · Personal account
As of 1w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · osv@v1
deps.dev advisories
Not queried
deps.dev@v1
Not queried
deps.dev@v1
OpenSSF Scorecard
Not queried
openssf-scorecard@v1
Not queried
openssf-scorecard@v1

Tagline

airllm
AirLLM 70B inference with single 4GB GPU
anubis-oss
Local LLM Testing & Benchmarking for Apple Silicon

Stars

airllm
24k
anubis-oss
198

Forks

airllm
2.7k
anubis-oss
12

Open issues

airllm
115
anubis-oss
4

Language

airllm
Jupyter Notebook
anubis-oss
Swift

Adopt for

airllm
AirLLM is a notable framework designed specifically for running large language models on low-resource hardware, such as a single 4GB GPU.
anubis-oss
Anubis-oss, specifically tailored for Apple Silicon devices using Swift, is distinguished by its focus on local large language model evaluation and testing within the macOS environment.

Persona

airllm
-
anubis-oss
-

Runtime

airllm
-
anubis-oss
-

License

airllm
Apache-2.0
anubis-oss
GPL-3.0 license ensures that any derivative works related to anubis-oss must also be open source under the same licensing terms.

Last pushed

airllm
Jul 23, 2026
anubis-oss
Jun 18, 2026

Categories

airllm
Inference & Serving
anubis-oss
Evaluation & Observability, Inference & Serving

Trust and health

Maintenance

airllm
Very active (96%)
anubis-oss
Steady (60%)

Days since push

airllm
5d
anubis-oss
56d

Open issues (now)

airllm
115
anubis-oss
4

OSV dependency advisories

airllm
Published findings
anubis-oss
No lockfile (source not queried)

Full report

anubis-oss
Trust report

Choose airllm if…

  • airllm is primarily Jupyter Notebook; anubis-oss is Swift.
  • License: airllm is Apache-2.0, anubis-oss is GPL-3.0.
  • Pricing: Free and open-source under the Apache-2.0 license; however, infrastructure costs apply..
  • Requirements: Min 16 GB RAM; A single 4GB GPU is sufficient for using this framework to run large language model inferences..
  • Tags unique to airllm: chinese-llm, chinese-nlp, finetune, generative-ai.
  • If you have limited hardware resources but need to perform inferences on large language models (like the 70B parameter model that AirLLM supports), use AirLLM.

When NOT to use airllm

  • Avoid using AirLLM if you require models to run on higher-end GPUs or multiple GPU clusters, as its strength lies in low-resource efficiency.
  • Do not use AirLLM if you are working primarily with non-Chinese language datasets and models, since support for other languages may be less optimized compared to competition.

Choose anubis-oss if…

  • anubis-oss is primarily Swift; airllm is Jupyter Notebook.
  • License: anubis-oss is GPL-3.0, airllm is Apache-2.0.
  • Pricing: The tool is free and open-source with no monetary costs for usage or distribution..
  • Requirements: Min 8 GB RAM.
  • Tags unique to anubis-oss: apple-silicon, benchmarking, gpu, inference.
  • Also covers Evaluation & Observability.
  • When developing and evaluating large language models intended to run natively on Apple Silicon hardware.

When NOT to use anubis-oss

  • If your development does not involve Apple Silicon or macOS environments as Anubis-oss is tightly integrated with these platforms.
  • When preferring a language other than Swift, since Anubis-oss depends on this for its operations.

Explore

Sources

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

GitHub stars on cards: airllm 24k · anubis-oss 198 (synced Jul 28, 2026).

Common questions

What is the difference between airllm and anubis-oss?
airllm: AirLLM 70B inference with single 4GB GPU. anubis-oss: Local LLM Testing & Benchmarking for Apple Silicon. See the comparison table for live GitHub stats and shared categories.
When should I choose airllm over anubis-oss?
Choose airllm over anubis-oss when airllm is primarily Jupyter Notebook; anubis-oss is Swift; License: airllm is Apache-2.0, anubis-oss is GPL-3.0; Pricing: Free and open-source under the Apache-2.0 license; however, infrastructure costs apply.; Requirements: Min 16 GB RAM; A single 4GB GPU is sufficient for using this framework to run large language model inferences.; Tags unique to airllm: chinese-llm, chinese-nlp, finetune, generative-ai; If you have limited hardware resources but need to perform inferences on large language models (like the 70B parameter model that AirLLM supports), use AirLLM.
When should I choose anubis-oss over airllm?
Choose anubis-oss over airllm when anubis-oss is primarily Swift; airllm is Jupyter Notebook; License: anubis-oss is GPL-3.0, airllm is Apache-2.0; Pricing: The tool is free and open-source with no monetary costs for usage or distribution.; Requirements: Min 8 GB RAM; Tags unique to anubis-oss: apple-silicon, benchmarking, gpu, inference; Also covers Evaluation & Observability; When developing and evaluating large language models intended to run natively on Apple Silicon hardware.
When should I avoid airllm?
Avoid using AirLLM if you require models to run on higher-end GPUs or multiple GPU clusters, as its strength lies in low-resource efficiency. Do not use AirLLM if you are working primarily with non-Chinese language datasets and models, since support for other languages may be less optimized compared to competition.
When should I avoid anubis-oss?
If your development does not involve Apple Silicon or macOS environments as Anubis-oss is tightly integrated with these platforms. When preferring a language other than Swift, since Anubis-oss depends on this for its operations.
Is airllm or anubis-oss more popular on GitHub?
airllm has more GitHub stars (24,183 vs 198). Stars measure visibility, not whether either tool fits your constraints.
Are airllm and anubis-oss open source?
Yes - both are open-source projects on GitHub (airllm: Apache-2.0, anubis-oss: GPL-3.0).
Where can I find alternatives to airllm or anubis-oss?
GraphCanon lists graph-backed alternatives at airllm alternatives and anubis-oss alternatives (airllm markdown twin, anubis-oss 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, airllm or anubis-oss?
airllm: Very active. anubis-oss: Steady. 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 airllm and anubis-oss?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: airllm trust report; anubis-oss trust report.

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