Home/Compare/budgetml vs airllm

Comparison

budgetml vs airllm

Verdict

Pick budgetml when budgetml is primarily Python; airllm is Jupyter Notebook; pick airllm when airllm is primarily Jupyter Notebook; budgetml is Python.

Markdown twin · budgetml alternatives · airllm alternatives

GraphCanon updated today

budgetml logo

budgetml

ebhy/budgetml

1.3kpushed Feb 12, 2024
vs
airllm logo

airllm

lyogavin/airllm

22kpushed Jul 11, 2026

Trust & integrity

Signalbudgetmlairllm
Maintenance
Dormant (880d since push)
As of today · github_public_v1
Very active (0d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
No criticals
As of today · osv@v1
4 low (4 low)
As of 2d · osv@v1

Tagline

budgetml
Deploy a ML inference service on a budget in less than 10 lines of code.
airllm
AirLLM 70B inference with single 4GB GPU

Stars

budgetml
1.3k
airllm
22k

Forks

budgetml
65
airllm
2.6k

Open issues

budgetml
4
airllm
106

Language

budgetml
Python
airllm
Jupyter Notebook

Adopt for

budgetml
-
airllm
AirLLM is a notable framework designed specifically for running large language models on low-resource hardware, such as a single 4GB GPU.

Persona

budgetml
-
airllm
-

Runtime

budgetml
-
airllm
-

License

budgetml
Apache-2.0
airllm
Apache-2.0

Last pushed

budgetml
Feb 12, 2024
airllm
Jul 11, 2026

Categories

budgetml
Inference & Serving
airllm
Inference & Serving

Trust and health

Maintenance

budgetml
Dormant (18%)
airllm
Very active (96%)

Days since push

budgetml
880d
airllm
0d

Open issues (now)

budgetml
4
airllm
106

Owner type

budgetml
Organization
airllm
User

Security scan

budgetml
No criticals
airllm
4 low (4 low)

Full report

budgetml
Trust report

Choose budgetml if…

  • budgetml is primarily Python; airllm is Jupyter Notebook.
  • Tags unique to budgetml: data-science, deployment, machine-learning, python.
  • Leaner open-issue backlog (4).

When NOT to use budgetml

  • Last GitHub push was 880 days ago (dormant maintenance, Feb 12, 2024). Validate activity before betting a new project on budgetml.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.

Choose airllm if…

  • airllm is primarily Jupyter Notebook; budgetml is Python.
  • 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: llama, chinese-llm, llm, instruct-gpt.
  • 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.

Explore

Sources

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

GitHub stars on cards: budgetml 1.3k · airllm 22k (synced Jul 11, 2026).

Common questions

What is the difference between budgetml and airllm?
budgetml: Deploy a ML inference service on a budget in less than 10 lines of code.. airllm: AirLLM 70B inference with single 4GB GPU. See the comparison table for live GitHub stats and shared categories.
When should I choose budgetml over airllm?
Choose budgetml over airllm when budgetml is primarily Python; airllm is Jupyter Notebook; Tags unique to budgetml: data-science, deployment, machine-learning, python; Leaner open-issue backlog (4).
When should I choose airllm over budgetml?
Choose airllm over budgetml when airllm is primarily Jupyter Notebook; budgetml is Python; 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: llama, chinese-llm, llm, instruct-gpt; 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 avoid budgetml?
Last GitHub push was 880 days ago (dormant maintenance, Feb 12, 2024). Validate activity before betting a new project on budgetml. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
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.
Is budgetml or airllm more popular on GitHub?
airllm has more GitHub stars (22,399 vs 1,343). Stars measure visibility, not whether either tool fits your constraints.
Are budgetml and airllm open source?
Yes - both are open-source projects on GitHub (budgetml: Apache-2.0, airllm: Apache-2.0).
Where can I find alternatives to budgetml or airllm?
GraphCanon lists graph-backed alternatives at budgetml alternatives and airllm alternatives (budgetml markdown twin, airllm 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, budgetml or airllm?
budgetml: Dormant. airllm: Very 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 budgetml and airllm?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: budgetml trust report; airllm trust report.