Comparison
thinkgpt vs awesome
Verdict
Pick thinkgpt when license: thinkgpt is Apache-2.0, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, thinkgpt is Apache-2.0.
Markdown twin · thinkgpt alternatives · awesome alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | thinkgpt | awesome |
|---|---|---|
| Maintenance | Dormant (778d 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) | No lockfile As of today · none | No lockfile As of today · none |
Tagline
- thinkgpt
- Agent techniques to augment your LLM and push it beyong its limits
- awesome
- 😎 Curated list of awesome topics including hardware resources
Stars
- thinkgpt
- 1.6k
- awesome
- 484k
Forks
- thinkgpt
- 133
- awesome
- 36k
Open issues
- thinkgpt
- 16
- awesome
- 92
Language
- thinkgpt
- Python
- awesome
- -
Adopt for
- thinkgpt
- -
- awesome
- -
Persona
- thinkgpt
- -
- awesome
- -
Runtime
- thinkgpt
- -
- awesome
- -
License
- thinkgpt
- Apache-2.0
- awesome
- CC0-1.0
Last pushed
- thinkgpt
- May 23, 2024
- awesome
- Jun 30, 2026
Categories
- thinkgpt
- AI Agents, LLM Frameworks
- awesome
- LLM Frameworks
Trust and health
Maintenance
- thinkgpt
- Dormant (18%)
- awesome
- Active (82%)
Days since push
- thinkgpt
- 778d
- awesome
- 11d
Open issues (now)
- thinkgpt
- 16
- awesome
- 92
Owner type
- thinkgpt
- Organization
- awesome
- User
Full report
- thinkgpt
- Trust report
- awesome
- Trust report
Choose thinkgpt if…
- License: thinkgpt is Apache-2.0, awesome is CC0-1.0.
- Tags unique to thinkgpt: python.
- Also covers AI Agents.
When NOT to use thinkgpt
- Last GitHub push was 779 days ago (dormant maintenance, May 23, 2024). Validate activity before betting a new project on thinkgpt.
- 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.
Choose awesome if…
- License: awesome is CC0-1.0, thinkgpt is Apache-2.0.
- Tags unique to awesome: resources, awesome-list.
- More GitHub stars (484k vs 1.6k) - 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (jina-ai/thinkgpt) · observed Jul 11, 2026
- GitHub forks (jina-ai/thinkgpt) · observed Jul 11, 2026
- Last push (jina-ai/thinkgpt) · observed May 23, 2024
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (sindresorhus/awesome) · observed Jul 11, 2026
- GitHub forks (sindresorhus/awesome) · observed Jul 11, 2026
- Last push (sindresorhus/awesome) · observed Jun 30, 2026
- License file (CC0-1.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: thinkgpt 1.6k · awesome 484k (synced Jul 11, 2026).
Common questions
- What is the difference between thinkgpt and awesome?
- thinkgpt: Agent techniques to augment your LLM and push it beyong its limits. awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories.
- When should I choose thinkgpt over awesome?
- Choose thinkgpt over awesome when License: thinkgpt is Apache-2.0, awesome is CC0-1.0; Tags unique to thinkgpt: python; Also covers AI Agents.
- When should I choose awesome over thinkgpt?
- Choose awesome over thinkgpt when License: awesome is CC0-1.0, thinkgpt is Apache-2.0; Tags unique to awesome: resources, awesome-list; More GitHub stars (484k vs 1.6k) - visibility, not fit.
- When should I avoid thinkgpt?
- Last GitHub push was 779 days ago (dormant maintenance, May 23, 2024). Validate activity before betting a new project on thinkgpt. 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.
- 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 thinkgpt or awesome more popular on GitHub?
- awesome has more GitHub stars (484,026 vs 1,583). Stars measure visibility, not whether either tool fits your constraints.
- Are thinkgpt and awesome open source?
- Yes - both are open-source projects on GitHub (thinkgpt: Apache-2.0, awesome: CC0-1.0).
- Where can I find alternatives to thinkgpt or awesome?
- GraphCanon lists graph-backed alternatives at thinkgpt alternatives and awesome alternatives (thinkgpt 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, thinkgpt or awesome?
- thinkgpt: Dormant. 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 thinkgpt and awesome?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: thinkgpt trust report; awesome trust report.