Comparison
nas-env vs awesome
Verdict
Pick nas-env when license: nas-env is MIT, awesome is CC0-1.0; pick awesome when license: awesome is CC0-1.0, nas-env is MIT.
Markdown twin · nas-env alternatives · awesome alternatives
GraphCanon updated today
Trust & integrity
| Signal | nas-env | awesome |
|---|---|---|
| Maintenance | Dormant (2259d since push) As of today · github_public_v1 | Active (11d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Personal 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
- nas-env
- A simple OpenAI Gym environment for Neural Architecture Search (NAS)
- awesome
- 😎 Curated list of awesome topics including hardware resources
Stars
- nas-env
- 31
- awesome
- 484k
Forks
- nas-env
- 3
- awesome
- 36k
Open issues
- nas-env
- 0
- awesome
- 92
Language
- nas-env
- Python
- awesome
- -
Adopt for
- nas-env
- -
- awesome
- -
Persona
- nas-env
- -
- awesome
- -
Runtime
- nas-env
- -
- awesome
- -
License
- nas-env
- MIT
- awesome
- CC0-1.0
Last pushed
- nas-env
- May 4, 2020
- awesome
- Jun 30, 2026
Categories
- nas-env
- LLM Frameworks
- awesome
- LLM Frameworks
Trust and health
Maintenance
- nas-env
- Dormant (18%)
- awesome
- Active (82%)
Days since push
- nas-env
- 2259d
- awesome
- 11d
Open issues (now)
- nas-env
- 0
- awesome
- 92
Full report
- nas-env
- Trust report
- awesome
- Trust report
Choose nas-env if…
- License: nas-env is MIT, awesome is CC0-1.0.
- Tags unique to nas-env: neural-architecture-search, reinforcement-learning, python, openai-gym.
- Leaner open-issue backlog (0).
When NOT to use nas-env
- Last GitHub push was 2259 days ago (dormant maintenance, May 4, 2020). Validate activity before betting a new project on nas-env.
- 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, nas-env is MIT.
- Tags unique to awesome: resources, awesome-list.
- More GitHub stars (484k vs 31) - 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 (gomerudo/nas-env) · observed Jul 11, 2026
- GitHub forks (gomerudo/nas-env) · observed Jul 11, 2026
- Last push (gomerudo/nas-env) · observed May 4, 2020
- License file (MIT) · 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: nas-env 31 · awesome 484k (synced Jul 11, 2026).
Common questions
- What is the difference between nas-env and awesome?
- nas-env: A simple OpenAI Gym environment for Neural Architecture Search (NAS). awesome: 😎 Curated list of awesome topics including hardware resources. See the comparison table for live GitHub stats and shared categories.
- When should I choose nas-env over awesome?
- Choose nas-env over awesome when License: nas-env is MIT, awesome is CC0-1.0; Tags unique to nas-env: neural-architecture-search, reinforcement-learning, python, openai-gym; Leaner open-issue backlog (0).
- When should I choose awesome over nas-env?
- Choose awesome over nas-env when License: awesome is CC0-1.0, nas-env is MIT; Tags unique to awesome: resources, awesome-list; More GitHub stars (484k vs 31) - visibility, not fit.
- When should I avoid nas-env?
- Last GitHub push was 2259 days ago (dormant maintenance, May 4, 2020). Validate activity before betting a new project on nas-env. 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 nas-env or awesome more popular on GitHub?
- awesome has more GitHub stars (484,026 vs 31). Stars measure visibility, not whether either tool fits your constraints.
- Are nas-env and awesome open source?
- Yes - both are open-source projects on GitHub (nas-env: MIT, awesome: CC0-1.0).
- Where can I find alternatives to nas-env or awesome?
- GraphCanon lists graph-backed alternatives at nas-env alternatives and awesome alternatives (nas-env 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, nas-env or awesome?
- nas-env: 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 nas-env and awesome?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: nas-env trust report; awesome trust report.