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Comparison

core vs awesome

Verdict

Pick core when license: core is GPL-3.0, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, core is GPL-3.0.

Markdown twin · core alternatives · awesome alternatives

GraphCanon updated today

core logo

core

cheshire-cat-ai/core

★ 3.1kpushed Jul 8, 2026
vs
awesome logo

awesome

sindresorhus/awesome

★ 484kpushed Jun 30, 2026

Trust & integrity

Signalcoreawesome
Maintenance
Very active (2d since push)
As of today · github_public_v1
Active (11d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Personal account
As of today · github_public_v1
Security (OSV)
2 low (2 low)
As of today · mcp_manifest@v1
No lockfile
As of today · none
core trust reportawesome trust reportTrust methodology

Tagline

core
AI agent microservice
awesome
😎 Curated list of awesome topics including hardware resources

Stars

core
3.1k
awesome
484k

Forks

core
410
awesome
36k

Open issues

core
4
awesome
92

Language

core
Python
awesome
-

Adopt for

core
-
awesome
-

Persona

core
-
awesome
-

Runtime

core
-
awesome
-

License

core
GPL-3.0
awesome
CC0-1.0

Last pushed

core
Jul 8, 2026
awesome
Jun 30, 2026

Categories

core
AI Agents, LLM Frameworks, Vector Databases
awesome
LLM Frameworks

Trust and health

Maintenance

core
Very active (96%)
awesome
Active (82%)

Days since push

core
2d
awesome
11d

Open issues (now)

core
4
awesome
92

Owner type

core
Organization
awesome
User

Security scan

core
2 low (2 low)
awesome
No lockfile

Full report

core
Trust report
awesome
Trust report

Choose core if…

  • License: core is GPL-3.0, awesome is CC0-1.0.
  • Tags unique to core: ag-ui-protocol, agent, ai, assistant.
  • Also covers AI Agents, Vector Databases.

When NOT to use core

  • 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.
GitHubDetails

Choose awesome if…

  • License: awesome is CC0-1.0, core is GPL-3.0.
  • Tags unique to awesome: awesome-list, resources.
  • More GitHub stars (484k vs 3.1k) - visibility, not fit.

When NOT to use awesome

  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Explore

core trust report →awesome trust report →AI Agents category →LLM Frameworks category →Vector Databases 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: core 3.1k · awesome 484k (synced Jul 11, 2026).

Common questions

What is the difference between core and awesome?
core: AI agent microservice. awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories.
When should I choose core over awesome?
Choose core over awesome when License: core is GPL-3.0, awesome is CC0-1.0; Tags unique to core: ag-ui-protocol, agent, ai, assistant; Also covers AI Agents, Vector Databases.
When should I choose awesome over core?
Choose awesome over core when License: awesome is CC0-1.0, core is GPL-3.0; Tags unique to awesome: awesome-list, resources; More GitHub stars (484k vs 3.1k) - visibility, not fit.
When should I avoid core?
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 awesome?
LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is core or awesome more popular on GitHub?
awesome has more GitHub stars (484,026 vs 3,072). Stars measure visibility, not whether either tool fits your constraints.
Are core and awesome open source?
Yes - both are open-source projects on GitHub (core: GPL-3.0, awesome: CC0-1.0).
Where can I find alternatives to core or awesome?
GraphCanon lists graph-backed alternatives at core alternatives and awesome alternatives (core markdown twin, awesome 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, core or awesome?
core: Very active. awesome: 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 core and awesome?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: core trust report; awesome trust report.