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Comparison

LLM-VM vs hello-agents

Verdict

Pick LLM-VM when license: LLM-VM is MIT, hello-agents is Other; pick hello-agents when license: hello-agents is Other, LLM-VM is MIT.

Markdown twin · LLM-VM alternatives · hello-agents alternatives

GraphCanon updated today

LLM-VM logo

LLM-VM

anarchy-ai/LLM-VM

★ 491pushed May 14, 2024
vs
hello-agents logo

hello-agents

datawhalechina/hello-agents

★ 65kpushed Jul 10, 2026

Trust & integrity

SignalLLM-VMhello-agents
Maintenance
Dormant (788d 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 · Organization account
As of today · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of today · none
LLM-VM trust reporthello-agents trust reportTrust methodology

Tagline

LLM-VM
irresponsible innovation. Try now at https://chat.dev/
hello-agents
Course on building intelligent agents from scratch

Stars

LLM-VM
491
hello-agents
65k

Forks

LLM-VM
136
hello-agents
8.1k

Open issues

LLM-VM
130
hello-agents
144

Language

LLM-VM
Python
hello-agents
Python

Adopt for

LLM-VM
-
hello-agents
hello-agents is a comprehensive guide and hands-on tutorial for developing AI agents using LLMs (Large Language Models) and RAG methods.

Persona

LLM-VM
-
hello-agents
-

Runtime

LLM-VM
-
hello-agents
-

License

LLM-VM
MIT
hello-agents
hello-agents is covered under an unconventional license which may require further review before usage.

Last pushed

LLM-VM
May 14, 2024
hello-agents
Jul 10, 2026

Categories

LLM-VM
LLM Frameworks, AI Agents, Model Training
hello-agents
AI Agents, LLM Frameworks

Trust and health

Maintenance

LLM-VM
Dormant (18%)
hello-agents
Very active (96%)

Days since push

LLM-VM
788d
hello-agents
0d

Open issues (now)

LLM-VM
130
hello-agents
144

Full report

LLM-VM
Trust report
hello-agents
Trust report

Choose LLM-VM if…

  • License: LLM-VM is MIT, hello-agents is Other.
  • Tags unique to LLM-VM: distillation-model, deep-learning, llm-local, artificial-intelligence.
  • Also covers Model Training.

When NOT to use LLM-VM

  • Last GitHub push was 788 days ago (dormant maintenance, May 14, 2024). Validate activity before betting a new project on LLM-VM.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
GitHubDetails

Choose hello-agents if…

  • License: hello-agents is Other, LLM-VM is MIT.
  • Requirements: Min 4 GB RAM; Python knowledge assumed.
  • Tags unique to hello-agents: rag, tutorial, agent.
  • You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.

When NOT to use hello-agents

  • Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application.
  • Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
GitHubDetails

Explore

LLM-VM trust report →hello-agents trust report →LLM Frameworks category →AI Agents category →Model Training 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: LLM-VM 491 · hello-agents 65k (synced Jul 11, 2026).

Common questions

What is the difference between LLM-VM and hello-agents?
LLM-VM: irresponsible innovation. Try now at https://chat.dev/. hello-agents: Course on building intelligent agents from scratch. See the comparison table for live GitHub stats and shared categories.
When should I choose LLM-VM over hello-agents?
Choose LLM-VM over hello-agents when License: LLM-VM is MIT, hello-agents is Other; Tags unique to LLM-VM: distillation-model, deep-learning, llm-local, artificial-intelligence; Also covers Model Training.
When should I choose hello-agents over LLM-VM?
Choose hello-agents over LLM-VM when License: hello-agents is Other, LLM-VM is MIT; Requirements: Min 4 GB RAM; Python knowledge assumed; Tags unique to hello-agents: rag, tutorial, agent; You should use hello-agents if you are interested in practical, step-by-step instructions on building intelligent agents from the ground up.
When should I avoid LLM-VM?
Last GitHub push was 788 days ago (dormant maintenance, May 14, 2024). Validate activity before betting a new project on LLM-VM. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
When should I avoid hello-agents?
Avoid using hello-agents if you are looking for a quick, superficial introduction to AI agents; this tool focuses heavily on in-depth learning and practical application. Do not opt for hello-agents if you want a more general AI development resource; unlike some competitors, it has a narrower focus specifically on agent creation with advanced methods like LLMs and RAG.
Is LLM-VM or hello-agents more popular on GitHub?
hello-agents has more GitHub stars (65,432 vs 491). Stars measure visibility, not whether either tool fits your constraints.
Are LLM-VM and hello-agents open source?
Yes - both are open-source projects on GitHub (LLM-VM: MIT, hello-agents: Other).
Where can I find alternatives to LLM-VM or hello-agents?
GraphCanon lists graph-backed alternatives at LLM-VM alternatives and hello-agents alternatives (LLM-VM markdown twin, hello-agents 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, LLM-VM or hello-agents?
LLM-VM: Dormant. hello-agents: 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 LLM-VM and hello-agents?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LLM-VM trust report; hello-agents trust report.