Comparison
LazyLLM vs agent-kernel
Verdict
Pick LazyLLM if critical facts for LazyLLM; pick agent-kernel if agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A.
Markdown twin · LazyLLM alternatives · agent-kernel alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | LazyLLM | agent-kernel |
|---|---|---|
| Maintenance | Very active (0d since push) As of 1w · github_public_v1 | Very active (2d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 1w · github_public_v1 | Not a fork · Organization 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
- LazyLLM
- Easiest and laziest way for building multi-agent LLMs applications.
- agent-kernel
- The Operating System for Scalable Enterprise AI Agents
Stars
- LazyLLM
- 3.9k
- agent-kernel
- 113
Forks
- LazyLLM
- 404
- agent-kernel
- 60
Open issues
- LazyLLM
- 41
- agent-kernel
- 128
Language
- LazyLLM
- Python
- agent-kernel
- Python
Adopt for
- LazyLLM
- Critical facts for LazyLLM
- agent-kernel
- Agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A.
Persona
- LazyLLM
- -
- agent-kernel
- -
Runtime
- LazyLLM
- -
- agent-kernel
- -
License
- LazyLLM
- Apache-2.0
- agent-kernel
- Apache-2.0
Last pushed
- LazyLLM
- Aug 7, 2026
- agent-kernel
- Aug 7, 2026
Categories
- LazyLLM
- AI Agents, Model Training
- agent-kernel
- AI Agents
Trust and health
Days since push
- LazyLLM
- 0d
- agent-kernel
- 2d
Open issues (now)
- LazyLLM
- 41
- agent-kernel
- 128
OSV dependency advisories
- LazyLLM
- Published findings
- agent-kernel
- No lockfile (source not queried)
Full report
- LazyLLM
- Trust report
- agent-kernel
- Trust report
Shared compatibility
- Python · LazyLLM: Python runtime · agent-kernel: Python runtime
Choose LazyLLM if…
- 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.
Choose agent-kernel if…
- Requirements: It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module..
- Tags unique to agent-kernel: a2a, adk, aws, azure.
- If you require seamless scalability across different cloud providers like AWS and Azure without lock-in or rewrites.
When NOT to use agent-kernel
- If your project is confined to a single, specific AI framework which doesn't require the flexibility Agent-kernel offers.
- When you do not have Python version 3.12 - 3.13.x, as it's the required runtime environment.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (LazyAGI/LazyLLM) · observed Aug 8, 2026
- GitHub forks (LazyAGI/LazyLLM) · observed Aug 8, 2026
- Last push (LazyAGI/LazyLLM) · observed Aug 7, 2026
- License file (Apache-2.0) · observed Aug 8, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (yaalalabs/agent-kernel) · observed Aug 9, 2026
- GitHub forks (yaalalabs/agent-kernel) · observed Aug 9, 2026
- Last push (yaalalabs/agent-kernel) · observed Aug 7, 2026
- License file (Apache-2.0) · observed Aug 9, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: LazyLLM 3.9k · agent-kernel 113 (synced Aug 8, 2026).
Common questions
- What is the difference between LazyLLM and agent-kernel?
- LazyLLM: Easiest and laziest way for building multi-agent LLMs applications.. agent-kernel: The Operating System for Scalable Enterprise AI Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose LazyLLM over agent-kernel?
- Choose LazyLLM over agent-kernel when 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 choose agent-kernel over LazyLLM?
- Choose agent-kernel over LazyLLM when Requirements: It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module.; Tags unique to agent-kernel: a2a, adk, aws, azure; If you require seamless scalability across different cloud providers like AWS and Azure without lock-in or rewrites.
- 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.
- When should I avoid agent-kernel?
- If your project is confined to a single, specific AI framework which doesn't require the flexibility Agent-kernel offers. When you do not have Python version 3.12 - 3.13.x, as it's the required runtime environment.
- Is LazyLLM or agent-kernel more popular on GitHub?
- LazyLLM has more GitHub stars (3,866 vs 113). Stars measure visibility, not whether either tool fits your constraints.
- Are LazyLLM and agent-kernel open source?
- Yes - both are open-source projects on GitHub (LazyLLM: Apache-2.0, agent-kernel: Apache-2.0).
- Where can I find alternatives to LazyLLM or agent-kernel?
- GraphCanon lists graph-backed alternatives at LazyLLM alternatives and agent-kernel alternatives (LazyLLM markdown twin, agent-kernel 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, LazyLLM or agent-kernel?
- LazyLLM: Very active. agent-kernel: 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 LazyLLM and agent-kernel?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: LazyLLM trust report; agent-kernel trust report.