Home/Compare/CoDA-Bench vs AutoGPT

Comparison

CoDA-Bench vs AutoGPT

Verdict

Pick CoDA-Bench when license: CoDA-Bench is MIT, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, CoDA-Bench is MIT.

Markdown twin · CoDA-Bench alternatives · AutoGPT alternatives

GraphCanon updated today

CoDA-Bench logo

CoDA-Bench

ruc-datalab/CoDA-Bench

39pushed Jun 17, 2026
vs
AutoGPT logo

AutoGPT

Significant-Gravitas/AutoGPT

185kpushed Jul 11, 2026

Trust & integrity

SignalCoDA-BenchAutoGPT
Maintenance
Active (28d since push)
As of today · github_public_v1
Very active (0d since push)
As of 4d · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of 4d · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of today · osv@v1
No lockfile (source not queried)
As of 4d · 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

CoDA-Bench
CoDA-Bench is a benchmark for code agents on data-intensive tasks. 🎈代码智能体能搞定数据密集型任务吗?
AutoGPT
AutoGPT is the vision of accessible AI for everyone, to use and to build on.

Stars

CoDA-Bench
39
AutoGPT
185k

Forks

CoDA-Bench
0
AutoGPT
46k

Open issues

CoDA-Bench
0
AutoGPT
494

Language

CoDA-Bench
Python
AutoGPT
Python

Adopt for

CoDA-Bench
-
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

CoDA-Bench
-
AutoGPT
-

Runtime

CoDA-Bench
-
AutoGPT
-

License

CoDA-Bench
MIT
AutoGPT
Other

Last pushed

CoDA-Bench
Jun 17, 2026
AutoGPT
Jul 11, 2026

Categories

CoDA-Bench
AI Agents, LLM Frameworks, Vector Databases
AutoGPT
AI Agents, LLM Frameworks

Trust and health

Maintenance

CoDA-Bench
Active (82%)
AutoGPT
Very active (96%)

Days since push

CoDA-Bench
28d
AutoGPT
0d

Open issues (now)

CoDA-Bench
0
AutoGPT
494

Full report

CoDA-Bench
Trust report

Choose CoDA-Bench if…

  • License: CoDA-Bench is MIT, AutoGPT is Other.
  • Tags unique to CoDA-Bench: agent, agentic, benchmark, code-agent.
  • Also covers Vector Databases.

When NOT to use CoDA-Bench

  • 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.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

Choose AutoGPT if…

  • License: AutoGPT is Other, CoDA-Bench is MIT.
  • Tags unique to AutoGPT: agents, artificial-intelligence, autonomous-agents, claude.
  • 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: CoDA-Bench 39 · AutoGPT 185k (synced Jul 15, 2026).

Common questions

What is the difference between CoDA-Bench and AutoGPT?
CoDA-Bench: CoDA-Bench is a benchmark for code agents on data-intensive tasks. 🎈代码智能体能搞定数据密集型任务吗?. 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 CoDA-Bench over AutoGPT?
Choose CoDA-Bench over AutoGPT when License: CoDA-Bench is MIT, AutoGPT is Other; Tags unique to CoDA-Bench: agent, agentic, benchmark, code-agent; Also covers Vector Databases.
When should I choose AutoGPT over CoDA-Bench?
Choose AutoGPT over CoDA-Bench when License: AutoGPT is Other, CoDA-Bench is MIT; Tags unique to AutoGPT: agents, artificial-intelligence, autonomous-agents, claude; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
When should I avoid CoDA-Bench?
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. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
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 CoDA-Bench or AutoGPT more popular on GitHub?
AutoGPT has more GitHub stars (185,464 vs 39). Stars measure visibility, not whether either tool fits your constraints.
Are CoDA-Bench and AutoGPT open source?
Yes - both are open-source projects on GitHub (CoDA-Bench: MIT, AutoGPT: Other).
Where can I find alternatives to CoDA-Bench or AutoGPT?
GraphCanon lists graph-backed alternatives at CoDA-Bench alternatives and AutoGPT alternatives (CoDA-Bench 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, CoDA-Bench or AutoGPT?
CoDA-Bench: 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 CoDA-Bench and AutoGPT?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: CoDA-Bench trust report; AutoGPT trust report.

Was this helpful?

Anonymous feedback helps us improve pages and translations.