Comparison
pytorch vs auto-maple
Verdict
Pick pytorch when tags unique to pytorch: autograd, deep-learning, gpu, neural-network; pick auto-maple when tags unique to auto-maple: ai, computer-vision, maplestory.
Markdown twin · pytorch alternatives · auto-maple alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | pytorch | auto-maple |
|---|---|---|
| Maintenance | Very active (0d since push) As of today · github_public_v1 | Slowing (197d 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 criticals As of today · osv@v1 | No criticals As of today · osv@v1 |
Tagline
- pytorch
- Tensors and Dynamic neural networks in Python with strong GPU acceleration
- auto-maple
- Artificial intelligence for MapleStory that uses machine learning and computer vision to navigate challenging in-game environments
Stars
- pytorch
- 102k
- auto-maple
- 671
Forks
- pytorch
- 28k
- auto-maple
- 321
Open issues
- pytorch
- 18k
- auto-maple
- 60
Language
- pytorch
- Python
- auto-maple
- Python
Adopt for
- pytorch
- -
- auto-maple
- -
Persona
- pytorch
- -
- auto-maple
- -
Runtime
- pytorch
- -
- auto-maple
- -
License
- pytorch
- Other
- auto-maple
- -
Last pushed
- pytorch
- Jul 11, 2026
- auto-maple
- Dec 26, 2025
Categories
- pytorch
- Computer Vision, Data & Retrieval, Model Training
- auto-maple
- Computer Vision, Developer Tools, Model Training
Trust and health
Maintenance
- pytorch
- Very active (96%)
- auto-maple
- Slowing (36%)
Days since push
- pytorch
- 0d
- auto-maple
- 197d
Open issues (now)
- pytorch
- 18k
- auto-maple
- 60
Owner type
- pytorch
- Organization
- auto-maple
- User
Full report
- pytorch
- Trust report
- auto-maple
- Trust report
Shared compatibility
- Python · pytorch: Python runtime · auto-maple: Python runtime
Choose pytorch if…
- Tags unique to pytorch: autograd, deep-learning, gpu, neural-network.
- Also covers Data & Retrieval.
- pytorch ships Docker support for self-hosted deployment.
When NOT to use pytorch
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Choose auto-maple if…
- Tags unique to auto-maple: ai, computer-vision, maplestory.
- Also covers Developer Tools.
- Leaner open-issue backlog (60).
When NOT to use auto-maple
- Last GitHub push was 198 days ago (slowing maintenance, Dec 26, 2025). Validate activity before betting a new project on auto-maple.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (pytorch/pytorch) · observed Jul 11, 2026
- GitHub forks (pytorch/pytorch) · observed Jul 11, 2026
- Last push (pytorch/pytorch) · observed Jul 11, 2026
- License file (Other) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (tanjeffreyz/auto-maple) · observed Jul 11, 2026
- GitHub forks (tanjeffreyz/auto-maple) · observed Jul 11, 2026
- Last push (tanjeffreyz/auto-maple) · observed Dec 26, 2025
- License file (unknown) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: pytorch 102k · auto-maple 671 (synced Jul 11, 2026).
Common questions
- What is the difference between pytorch and auto-maple?
- pytorch: Tensors and Dynamic neural networks in Python with strong GPU acceleration. auto-maple: Artificial intelligence for MapleStory that uses machine learning and computer vision to navigate challenging in-game environments. See the comparison table for live GitHub stats and shared categories.
- When should I choose pytorch over auto-maple?
- Choose pytorch over auto-maple when Tags unique to pytorch: autograd, deep-learning, gpu, neural-network; Also covers Data & Retrieval; pytorch ships Docker support for self-hosted deployment.
- When should I choose auto-maple over pytorch?
- Choose auto-maple over pytorch when Tags unique to auto-maple: ai, computer-vision, maplestory; Also covers Developer Tools; Leaner open-issue backlog (60).
- When should I avoid pytorch?
- Data & Retrieval: Skip a heavy ingestion framework when your corpus is small and static; a script plus the embedding API is enough. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- When should I avoid auto-maple?
- Last GitHub push was 198 days ago (slowing maintenance, Dec 26, 2025). Validate activity before betting a new project on auto-maple. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Is pytorch or auto-maple more popular on GitHub?
- pytorch has more GitHub stars (101,752 vs 671). Stars measure visibility, not whether either tool fits your constraints.
- Are pytorch and auto-maple open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to pytorch or auto-maple?
- GraphCanon lists graph-backed alternatives at pytorch alternatives and auto-maple alternatives (pytorch markdown twin, auto-maple 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, pytorch or auto-maple?
- pytorch: Very active. auto-maple: Slowing. 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 pytorch and auto-maple?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: pytorch trust report; auto-maple trust report.