--- title: "keras vs wandb" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/keras-team-keras-vs-wandb-wandb" tools: ["keras-team-keras", "wandb-wandb"] --- # keras vs wandb *GraphCanon updated Jul 12, 2026* ## 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. [keras](http://keras.io/) reports 64k GitHub stars, 20k forks, and 228 open issues, last pushed Jul 7, 2026. [wandb](https://wandb.ai) has 11k stars, 884 forks, and 898 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [keras's repository](https://github.com/keras-team/keras) and [wandb's repository](https://github.com/wandb/wandb). | | [keras](/tools/keras-team-keras.md) | [wandb](/tools/wandb-wandb.md) | | --- | --- | --- | | Tagline | Deep Learning for humans | The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production. | | Stars | 64,191 | 11,175 | | Forks | 19,752 | 884 | | Open issues | 228 | 898 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | Model Training | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [keras](/tools/keras-team-keras.md) | [wandb](/tools/wandb-wandb.md) | | --- | --- | --- | | Days since push | 4d | 0d | | Open issues (now) | 228 | 898 | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/keras-team-keras/trust.md) | [trust report](/tools/wandb-wandb/trust.md) | ## Shared compatibility - **Python**: [keras](/tools/keras-team-keras.md) - Python runtime; [wandb](/tools/wandb-wandb.md) - Python runtime ## Choose when ### Choose keras if… - License: keras is Apache-2.0, wandb is MIT. - Tags unique to keras: jax, machine-learning, neural-networks, python. - More GitHub stars (64k vs 11k) - visibility, not fit. ### Choose wandb if… - License: wandb is MIT, keras is Apache-2.0. - Tags unique to wandb: ai, collaboration, data-versioning, experiment-track. - Also covers Inference & Serving, LLM Frameworks. ## When NOT to use keras - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use wandb - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - 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. ## 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: jax, machine-learning, neural-networks, python; 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: ai, collaboration, data-versioning, experiment-track; Also covers Inference & Serving, 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. ### When should I avoid wandb? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. 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. ### 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](/tools/keras-team-keras/alternatives) and [wandb alternatives](/tools/wandb-wandb/alternatives) ([keras markdown twin](/tools/keras-team-keras/alternatives.md), [wandb markdown twin](/tools/wandb-wandb/alternatives.md)), 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](/compare/keras-team-keras-vs-wandb-wandb.md) 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](/tools/keras-team-keras/trust); [wandb trust report](/tools/wandb-wandb/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=keras-team-keras`](/api/graphcanon/graph?tool=keras-team-keras) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_