Comparison
keras vs wandb
Verdict
Pick keras when license: keras is Apache-2.0, wandb is MIT; pick wandb when license: wandb is MIT, keras is Apache-2.0.
Markdown twin · keras alternatives · wandb alternatives
GraphCanon updated today
Trust & integrity
| Signal | keras | wandb |
|---|---|---|
| Maintenance | Very active (4d since push) As of today · github_public_v1 | Very active (0d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of today · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| Security (OSV) | No criticals As of today · osv@v1 | No lockfile As of today · none |
Tagline
- keras
- Deep Learning for humans
- wandb
- The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Stars
- keras
- 64k
- wandb
- 11k
Forks
- keras
- 20k
- wandb
- 884
Open issues
- keras
- 228
- wandb
- 898
Language
- keras
- Python
- wandb
- Python
Adopt for
- keras
- -
- wandb
- -
Persona
- keras
- -
- wandb
- -
Runtime
- keras
- -
- wandb
- -
License
- keras
- Apache-2.0
- wandb
- MIT
Last pushed
- keras
- Jul 7, 2026
- wandb
- Jul 11, 2026
Categories
- keras
- Model Training, Inference & Serving
- wandb
- LLM Frameworks, Model Training, Inference & Serving
Trust and health
Days since push
- keras
- 4d
- wandb
- 0d
Open issues (now)
- keras
- 228
- wandb
- 898
Security scan
- keras
- No criticals
- wandb
- No lockfile
Full report
- keras
- Trust report
- wandb
- Trust report
Shared compatibility
- Python · keras: Python runtime · wandb: Python runtime
Choose keras if…
- License: keras is Apache-2.0, wandb is MIT.
- Tags unique to keras: neural-networks, machine-learning, python, pytorch.
- More GitHub stars (64k vs 11k) - visibility, not fit.
When NOT to use keras
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Choose wandb if…
- License: wandb is MIT, keras is Apache-2.0.
- Tags unique to wandb: collaboration, data-versioning, experiment-track, hyperparameter-search.
- Also covers LLM Frameworks.
When NOT to use wandb
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge.
- Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (keras-team/keras) · observed Jul 11, 2026
- GitHub forks (keras-team/keras) · observed Jul 11, 2026
- Last push (keras-team/keras) · observed Jul 7, 2026
- License file (Apache-2.0) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (wandb/wandb) · observed Jul 11, 2026
- GitHub forks (wandb/wandb) · observed Jul 11, 2026
- Last push (wandb/wandb) · observed Jul 11, 2026
- License file (MIT) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: keras 64k · wandb 11k (synced Jul 11, 2026).
Common questions
- What is the difference between keras and wandb?
- keras: Deep Learning for humans. wandb: The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.. See the comparison table for live GitHub stats and shared categories.
- When should I choose keras over wandb?
- Choose keras over wandb when License: keras is Apache-2.0, wandb is MIT; Tags unique to keras: neural-networks, machine-learning, python, pytorch; More GitHub stars (64k vs 11k) - visibility, not fit.
- When should I choose wandb over keras?
- Choose wandb over keras when License: wandb is MIT, keras is Apache-2.0; Tags unique to wandb: collaboration, data-versioning, experiment-track, hyperparameter-search; Also covers LLM Frameworks.
- When should I avoid keras?
- Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- When should I avoid wandb?
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic.
- Is keras or wandb more popular on GitHub?
- keras has more GitHub stars (64,191 vs 11,175). Stars measure visibility, not whether either tool fits your constraints.
- Are keras and wandb open source?
- Yes - both are open-source projects on GitHub (keras: Apache-2.0, wandb: MIT).
- Where can I find alternatives to keras or wandb?
- GraphCanon lists graph-backed alternatives at keras alternatives and wandb alternatives (keras markdown twin, wandb 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, keras or wandb?
- keras: Very active. wandb: 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 keras and wandb?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: keras trust report; wandb trust report.