Comparison
agentos vs LazyLLM
Verdict
Pick agentos if agentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript; pick LazyLLM if critical facts for LazyLLM.
Markdown twin · agentos alternatives · LazyLLM alternatives
GraphCanon updated Sep 20, 2026
6views this month
Trust & integrity
| Signal | agentos | LazyLLM |
|---|---|---|
| Maintenance | Very active (1d since push) As of Sep 20, 2026 · github_public_v1 | Very active (3d since push) As of Sep 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 7, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 2026 · 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
- agentos
- TypeScript AI agent framework providing cognitive memory and runtime tool forging with support for multi-agent orchestration
- LazyLLM
- Easiest and laziest way for building multi-agent LLMs applications.
Stars
- agentos
- 670
- LazyLLM
- 3.9k
Forks
- agentos
- 97
- LazyLLM
- 411
Open issues
- agentos
- 11
- LazyLLM
- 47
Language
- agentos
- TypeScript
- LazyLLM
- Python
Adopt for
- agentos
- AgentOS supports eleven LLM providers with runtime tool forging capabilities for cognitive memory in TypeScript.
- LazyLLM
- Critical facts for LazyLLM
Persona
- agentos
- -
- LazyLLM
- -
Runtime
- agentos
- -
- LazyLLM
- -
License
- agentos
- Apache-2.0
- LazyLLM
- Apache-2.0
Last pushed
- agentos
- Sep 18, 2026
- LazyLLM
- Sep 4, 2026
Categories
- agentos
- AI Agents
- LazyLLM
- AI Agents, Model Training
Trust and health
Days since push
- agentos
- 1d
- LazyLLM
- 3d
Open issues (now)
- agentos
- 11
- LazyLLM
- 47
Stars delta
- agentos
- +69 (30d)
- LazyLLM
- +14 (30d)
Open issues delta
- agentos
- +2 (30d)
- LazyLLM
- +6 (30d)
OSV dependency advisories
- agentos
- No lockfile (source not queried)
- LazyLLM
- Published findings
Full report
- agentos
- Trust report
- LazyLLM
- Trust report
Choose agentos if…
- agentos is primarily TypeScript; LazyLLM is Python.
- Tags unique to agentos: agent-framework, cognitive-memory, llm-orchestration, runtime-tool-generation.
- Need for cognitive memory and real-time tool generation in AI agents
When NOT to use agentos
- Preferring frameworks without multi-agent orchestration support
- Prioritizing environments with less than eleven LLM provider options
Choose LazyLLM if…
- LazyLLM is primarily Python; agentos is TypeScript.
- Pricing: LazyLLM is open-source under the Apache-2.0 license, making it free to use for both personal and commercial projects..
- Requirements: Min 8 GB RAM; Installation can be done via pip or from source. No Docker required, but a Python environment is necessary..
- Tags unique to LazyLLM: agents, ai-agent, deep-learning, framework.
- Also covers Model Training.
- - When you need a highly user-friendly framework specifically designed for building multi-agent LLM applications, emphasizing simplicity and streamlined installation.
When NOT to use LazyLLM
- - Avoid if you require extensive customization options or a more complex framework; LazyLLM's focus on being the 'laziest' way may mean it lacks advanced or specialized features found in other tools.
- - If you are working with non-Python environments, as LazyLLM is specifically language-oriented towards Python. Users needing cross-language support might not find LazyLLM suitable.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (framerslab/agentos) · observed Sep 20, 2026
- GitHub forks (framerslab/agentos) · observed Sep 20, 2026
- Last push (framerslab/agentos) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (LazyAGI/LazyLLM) · observed Sep 20, 2026
- GitHub forks (LazyAGI/LazyLLM) · observed Sep 20, 2026
- Last push (LazyAGI/LazyLLM) · observed Sep 4, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: agentos 670 · LazyLLM 3.9k (synced Sep 20, 2026).
Common questions
- What is the difference between agentos and LazyLLM?
- agentos: TypeScript AI agent framework providing cognitive memory and runtime tool forging with support for multi-agent orchestration. LazyLLM: Easiest and laziest way for building multi-agent LLMs applications.. See the comparison table for live GitHub stats and shared categories.
- When should I choose agentos over LazyLLM?
- Choose agentos over LazyLLM when agentos is primarily TypeScript; LazyLLM is Python; Tags unique to agentos: agent-framework, cognitive-memory, llm-orchestration, runtime-tool-generation; Need for cognitive memory and real-time tool generation in AI agents.
- When should I choose LazyLLM over agentos?
- Choose LazyLLM over agentos when LazyLLM is primarily Python; agentos is TypeScript; Pricing: LazyLLM is open-source under the Apache-2.0 license, making it free to use for both personal and commercial projects.; Requirements: Min 8 GB RAM; Installation can be done via pip or from source. No Docker required, but a Python environment is necessary.; Tags unique to LazyLLM: agents, ai-agent, deep-learning, framework; Also covers Model Training; - When you need a highly user-friendly framework specifically designed for building multi-agent LLM applications, emphasizing simplicity and streamlined installation.
- When should I avoid agentos?
- Preferring frameworks without multi-agent orchestration support Prioritizing environments with less than eleven LLM provider options
- When should I avoid LazyLLM?
- - Avoid if you require extensive customization options or a more complex framework; LazyLLM's focus on being the 'laziest' way may mean it lacks advanced or specialized features found in other tools. - If you are working with non-Python environments, as LazyLLM is specifically language-oriented towards Python. Users needing cross-language support might not find LazyLLM suitable.
- Is agentos or LazyLLM more popular on GitHub?
- LazyLLM has more GitHub stars (3,880 vs 670). Stars measure visibility, not whether either tool fits your constraints.
- Are agentos and LazyLLM open source?
- Yes - both are open-source projects on GitHub (agentos: Apache-2.0, LazyLLM: Apache-2.0).
- Where can I find alternatives to agentos or LazyLLM?
- GraphCanon lists graph-backed alternatives at agentos alternatives and LazyLLM alternatives (agentos markdown twin, LazyLLM 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, agentos or LazyLLM?
- agentos: Very active. LazyLLM: 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 agentos and LazyLLM?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentos trust report; LazyLLM trust report.