Comparison
AutoGPT vs fast-llm-security-guardrails
Verdict
Pick AutoGPT when license: AutoGPT is Other, fast-llm-security-guardrails is MIT; pick fast-llm-security-guardrails when license: fast-llm-security-guardrails is MIT, AutoGPT is Other.
Markdown twin · AutoGPT alternatives · fast-llm-security-guardrails alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | AutoGPT | fast-llm-security-guardrails |
|---|---|---|
| Maintenance | Very active (0d since push) As of 4d · github_public_v1 | Slowing (161d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 4d · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 4d · osv@v1 | Published findings As of today · 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
- AutoGPT
- AutoGPT is the vision of accessible AI for everyone, to use and to build on.
- fast-llm-security-guardrails
- The fastest Trust Layer for AI Agents
Stars
- AutoGPT
- 185k
- fast-llm-security-guardrails
- 153
Forks
- AutoGPT
- 46k
- fast-llm-security-guardrails
- 20
Open issues
- AutoGPT
- 494
- fast-llm-security-guardrails
- 0
Language
- AutoGPT
- Python
- fast-llm-security-guardrails
- Python
Adopt for
- AutoGPT
- AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude.
- fast-llm-security-guardrails
- -
Persona
- AutoGPT
- -
- fast-llm-security-guardrails
- -
Runtime
- AutoGPT
- -
- fast-llm-security-guardrails
- -
License
- AutoGPT
- Other
- fast-llm-security-guardrails
- MIT
Last pushed
- AutoGPT
- Jul 11, 2026
- fast-llm-security-guardrails
- Feb 3, 2026
Categories
- AutoGPT
- AI Agents, LLM Frameworks
- fast-llm-security-guardrails
- AI Agents, Inference & Serving, LLM Frameworks
Trust and health
Maintenance
- AutoGPT
- Very active (96%)
- fast-llm-security-guardrails
- Slowing (36%)
Days since push
- AutoGPT
- 0d
- fast-llm-security-guardrails
- 161d
Open issues (now)
- AutoGPT
- 494
- fast-llm-security-guardrails
- 0
OSV dependency advisories
- AutoGPT
- No lockfile (source not queried)
- fast-llm-security-guardrails
- Published findings
Full report
- AutoGPT
- Trust report
- fast-llm-security-guardrails
- Trust report
Choose AutoGPT if…
- License: AutoGPT is Other, fast-llm-security-guardrails is MIT.
- Tags unique to AutoGPT: agents, ai, artificial-intelligence, autonomous-agents.
- When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
When NOT to use AutoGPT
- Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework.
- If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools.
Choose fast-llm-security-guardrails if…
- License: fast-llm-security-guardrails is MIT, AutoGPT is Other.
- Tags unique to fast-llm-security-guardrails: ai-agent, ai-agents, ai-runtime, cx-agent.
- Also covers Inference & Serving.
When NOT to use fast-llm-security-guardrails
- Last GitHub push was 161 days ago (slowing maintenance, Feb 3, 2026). Validate activity before betting a new project on fast-llm-security-guardrails.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (Significant-Gravitas/AutoGPT) · observed Jul 11, 2026
- GitHub forks (Significant-Gravitas/AutoGPT) · observed Jul 11, 2026
- Last push (Significant-Gravitas/AutoGPT) · observed Jul 11, 2026
- License file (Other) · observed Jul 11, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (ZenGuard-AI/fast-llm-security-guardrails) · observed Jul 15, 2026
- GitHub forks (ZenGuard-AI/fast-llm-security-guardrails) · observed Jul 15, 2026
- Last push (ZenGuard-AI/fast-llm-security-guardrails) · observed Feb 3, 2026
- License file (MIT) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: AutoGPT 185k · fast-llm-security-guardrails 153 (synced Jul 11, 2026).
Common questions
- What is the difference between AutoGPT and fast-llm-security-guardrails?
- AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. fast-llm-security-guardrails: The fastest Trust Layer for AI Agents. See the comparison table for live GitHub stats and shared categories.
- When should I choose AutoGPT over fast-llm-security-guardrails?
- Choose AutoGPT over fast-llm-security-guardrails when License: AutoGPT is Other, fast-llm-security-guardrails is MIT; Tags unique to AutoGPT: agents, ai, artificial-intelligence, autonomous-agents; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
- When should I choose fast-llm-security-guardrails over AutoGPT?
- Choose fast-llm-security-guardrails over AutoGPT when License: fast-llm-security-guardrails is MIT, AutoGPT is Other; Tags unique to fast-llm-security-guardrails: ai-agent, ai-agents, ai-runtime, cx-agent; Also covers Inference & Serving.
- When should I avoid AutoGPT?
- Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools.
- When should I avoid fast-llm-security-guardrails?
- Last GitHub push was 161 days ago (slowing maintenance, Feb 3, 2026). Validate activity before betting a new project on fast-llm-security-guardrails. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Is AutoGPT or fast-llm-security-guardrails more popular on GitHub?
- AutoGPT has more GitHub stars (185,464 vs 153). Stars measure visibility, not whether either tool fits your constraints.
- Are AutoGPT and fast-llm-security-guardrails open source?
- Yes - both are open-source projects on GitHub (AutoGPT: Other, fast-llm-security-guardrails: MIT).
- Where can I find alternatives to AutoGPT or fast-llm-security-guardrails?
- GraphCanon lists graph-backed alternatives at AutoGPT alternatives and fast-llm-security-guardrails alternatives (AutoGPT markdown twin, fast-llm-security-guardrails 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, AutoGPT or fast-llm-security-guardrails?
- AutoGPT: Very active. fast-llm-security-guardrails: Slowing. 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 AutoGPT and fast-llm-security-guardrails?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AutoGPT trust report; fast-llm-security-guardrails trust report.