Home/Compare/dograh vs AutoGPT

Comparison

dograh vs AutoGPT

Verdict

Pick dograh when license: dograh is BSD-2-Clause, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, dograh is BSD-2-Clause.

Markdown twin · dograh alternatives · AutoGPT alternatives

GraphCanon updated today

dograh logo

dograh

dograh-hq/dograh

4.8kpushed Jul 11, 2026
vs
AutoGPT logo

AutoGPT

Significant-Gravitas/AutoGPT

185kpushed Jul 11, 2026

Trust & integrity

SignaldograhAutoGPT
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (0d since push)
As of 1d · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of 1d · github_public_v1
Security (OSV)
No lockfile
As of today · none
No lockfile
As of 1d · none

Tagline

dograh
Open source voice AI platform. Self-hosted alternative to Vapi and Retell. On Prem, BYOK across Speech to Speech or LLM/STT/TTS, with a visual workflow builder, MCP native and telephony support.
AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on.

Stars

dograh
4.8k
AutoGPT
185k

Forks

dograh
1.1k
AutoGPT
46k

Open issues

dograh
22
AutoGPT
494

Language

dograh
Python
AutoGPT
Python

Adopt for

dograh
-
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.

Persona

dograh
-
AutoGPT
-

Runtime

dograh
-
AutoGPT
-

License

dograh
BSD-2-Clause
AutoGPT
Other

Last pushed

dograh
Jul 11, 2026
AutoGPT
Jul 11, 2026

Categories

dograh
AI Agents, Inference & Serving, LLM Frameworks
AutoGPT
AI Agents, LLM Frameworks

Trust and health

Open issues (now)

dograh
22
AutoGPT
494

Full report

Choose dograh if…

  • License: dograh is BSD-2-Clause, AutoGPT is Other.
  • Tags unique to dograh: ai-calling, asterisk-ari, conversational-ai, inbound-calls.
  • Also covers Inference & Serving.

When NOT to use dograh

  • 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.

Choose AutoGPT if…

  • License: AutoGPT is Other, dograh is BSD-2-Clause.
  • Tags unique to AutoGPT: agentic-ai, agents, ai, artificial-intelligence.
  • 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.

Explore

Sources

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

GitHub stars on cards: dograh 4.8k · AutoGPT 185k (synced Jul 11, 2026).

Common questions

What is the difference between dograh and AutoGPT?
dograh: Open source voice AI platform. Self-hosted alternative to Vapi and Retell. On Prem, BYOK across Speech to Speech or LLM/STT/TTS, with a visual workflow builder, MCP native and telephony support.. AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. See the comparison table for live GitHub stats and shared categories.
When should I choose dograh over AutoGPT?
Choose dograh over AutoGPT when License: dograh is BSD-2-Clause, AutoGPT is Other; Tags unique to dograh: ai-calling, asterisk-ari, conversational-ai, inbound-calls; Also covers Inference & Serving.
When should I choose AutoGPT over dograh?
Choose AutoGPT over dograh when License: AutoGPT is Other, dograh is BSD-2-Clause; Tags unique to AutoGPT: agentic-ai, agents, ai, artificial-intelligence; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
When should I avoid dograh?
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.
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.
Is dograh or AutoGPT more popular on GitHub?
AutoGPT has more GitHub stars (185,464 vs 4,829). Stars measure visibility, not whether either tool fits your constraints.
Are dograh and AutoGPT open source?
Yes - both are open-source projects on GitHub (dograh: BSD-2-Clause, AutoGPT: Other).
Where can I find alternatives to dograh or AutoGPT?
GraphCanon lists graph-backed alternatives at dograh alternatives and AutoGPT alternatives (dograh markdown twin, AutoGPT 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, dograh or AutoGPT?
dograh: Very active. AutoGPT: 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 dograh and AutoGPT?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: dograh trust report; AutoGPT trust report.