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Comparison

awesome vs WeaveBench

Verdict

Pick awesome when license: awesome is CC0-1.0, WeaveBench is MIT; pick WeaveBench when license: WeaveBench is MIT, awesome is CC0-1.0.

Markdown twin · awesome alternatives · WeaveBench alternatives

GraphCanon updated today

awesome logo

awesome

sindresorhus/awesome

★ 484kpushed Jun 30, 2026
vs
WeaveBench logo

WeaveBench

weavebench/WeaveBench

★ 151pushed Jul 8, 2026

Trust & integrity

SignalawesomeWeaveBench
Maintenance
Active (11d since push)
As of today · github_public_v1
Very active (3d since push)
As of today · github_public_v1
Provenance
Not a fork · Personal 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
16 low (16 low)
As of today · osv@v1
awesome trust reportWeaveBench trust reportTrust methodology

Tagline

awesome
😎 Curated list of awesome topics including hardware resources
WeaveBench
WeaveBench: A Long-Horizon, Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces

Stars

awesome
484k
WeaveBench
151

Forks

awesome
36k
WeaveBench
0

Open issues

awesome
92
WeaveBench
3

Language

awesome
-
WeaveBench
Python

Adopt for

awesome
-
WeaveBench
-

Persona

awesome
-
WeaveBench
-

Runtime

awesome
-
WeaveBench
-

License

awesome
CC0-1.0
WeaveBench
MIT

Last pushed

awesome
Jun 30, 2026
WeaveBench
Jul 8, 2026

Categories

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

Trust and health

Maintenance

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

Days since push

awesome
11d
WeaveBench
3d

Open issues (now)

awesome
92
WeaveBench
3

Owner type

awesome
User
WeaveBench
Organization

Security scan

awesome
No lockfile
WeaveBench
16 low (16 low)

Full report

awesome
Trust report
WeaveBench
Trust report

Choose awesome if…

  • License: awesome is CC0-1.0, WeaveBench is MIT.
  • Tags unique to awesome: resources, awesome-list.
  • More GitHub stars (484k vs 151) - 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

Choose WeaveBench if…

  • License: WeaveBench is MIT, awesome is CC0-1.0.
  • Tags unique to WeaveBench: computer-use-agent, benchmark, python, agent-as-judge.
  • Also covers AI Agents, Vector Databases.

When NOT to use WeaveBench

  • AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
  • Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.
  • LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
GitHubDetails

Explore

awesome trust report →WeaveBench trust report →LLM Frameworks category →AI Agents 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: awesome 484k · WeaveBench 151 (synced Jul 11, 2026).

Common questions

What is the difference between awesome and WeaveBench?
awesome: 😎 Curated list of awesome topics including hardware resources. WeaveBench: WeaveBench: A Long-Horizon, Real-World Benchmark for Computer-Use Agents with Hybrid Interfaces. See the comparison table for live GitHub stats and shared categories.
When should I choose awesome over WeaveBench?
Choose awesome over WeaveBench when License: awesome is CC0-1.0, WeaveBench is MIT; Tags unique to awesome: resources, awesome-list; More GitHub stars (484k vs 151) - visibility, not fit.
When should I choose WeaveBench over awesome?
Choose WeaveBench over awesome when License: WeaveBench is MIT, awesome is CC0-1.0; Tags unique to WeaveBench: computer-use-agent, benchmark, python, agent-as-judge; Also covers AI Agents, Vector Databases.
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.
When should I avoid WeaveBench?
AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
Is awesome or WeaveBench more popular on GitHub?
awesome has more GitHub stars (484,026 vs 151). Stars measure visibility, not whether either tool fits your constraints.
Are awesome and WeaveBench open source?
Yes - both are open-source projects on GitHub (awesome: CC0-1.0, WeaveBench: MIT).
Where can I find alternatives to awesome or WeaveBench?
GraphCanon lists graph-backed alternatives at awesome alternatives and WeaveBench alternatives (awesome markdown twin, WeaveBench 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, awesome or WeaveBench?
awesome: Active. WeaveBench: 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 awesome and WeaveBench?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: awesome trust report; WeaveBench trust report.