GraphCanon
Home/Compare/AutoGPT vs blast

Comparison

AutoGPT vs blast

Verdict

Pick AutoGPT when license: AutoGPT is Other, blast is MIT; pick blast when license: blast is MIT, AutoGPT is Other.

Markdown twin · AutoGPT alternatives · blast alternatives

GraphCanon updated today

AutoGPT logo

AutoGPT

Significant-Gravitas/AutoGPT

★ 185kpushed Jul 11, 2026
vs
blast logo

blast

stanford-mast/blast

★ 776pushed May 29, 2026

Trust & integrity

SignalAutoGPTblast
Maintenance
Very active (0d since push)
As of today · github_public_v1
Steady (42d 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
AutoGPT trust reportblast trust reportTrust methodology

Tagline

AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on.
blast
Open-source VMs-as-a-service

Stars

AutoGPT
185k
blast
776

Forks

AutoGPT
46k
blast
50

Open issues

AutoGPT
494
blast
6

Language

AutoGPT
Python
blast
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.
blast
-

Persona

AutoGPT
-
blast
-

Runtime

AutoGPT
-
blast
-

License

AutoGPT
Other
blast
MIT

Last pushed

AutoGPT
Jul 11, 2026
blast
May 29, 2026

Categories

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

Trust and health

Maintenance

AutoGPT
Very active (96%)
blast
Steady (60%)

Days since push

AutoGPT
0d
blast
42d

Open issues (now)

AutoGPT
494
blast
6

Full report

AutoGPT
Trust report
blast
Trust report

Choose AutoGPT if…

  • License: AutoGPT is Other, blast is MIT.
  • Tags unique to AutoGPT: agents, llm, 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.
GitHubDetails

Choose blast if…

  • License: blast is MIT, AutoGPT is Other.
  • Tags unique to blast: python, browser-automation, llm-inference, ai-agents.
  • Also covers Inference & Serving.

When NOT to use blast

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
  • Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
GitHubDetails

Explore

AutoGPT trust report →blast trust report →AI Agents category →LLM Frameworks category →Inference & Serving 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: AutoGPT 185k · blast 776 (synced Jul 11, 2026).

Common questions

What is the difference between AutoGPT and blast?
AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. blast: Open-source VMs-as-a-service. See the comparison table for live GitHub stats and shared categories.
When should I choose AutoGPT over blast?
Choose AutoGPT over blast when License: AutoGPT is Other, blast is MIT; Tags unique to AutoGPT: agents, llm, 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 choose blast over AutoGPT?
Choose blast over AutoGPT when License: blast is MIT, AutoGPT is Other; Tags unique to blast: python, browser-automation, llm-inference, ai-agents; 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 blast?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Is AutoGPT or blast more popular on GitHub?
AutoGPT has more GitHub stars (185,464 vs 776). Stars measure visibility, not whether either tool fits your constraints.
Are AutoGPT and blast open source?
Yes - both are open-source projects on GitHub (AutoGPT: Other, blast: MIT).
Where can I find alternatives to AutoGPT or blast?
GraphCanon lists graph-backed alternatives at AutoGPT alternatives and blast alternatives (AutoGPT markdown twin, blast 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 blast?
AutoGPT: Very active. blast: Steady. 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 blast?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: AutoGPT trust report; blast trust report.