--- title: "ml-surveys vs jax" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/eugeneyan-ml-surveys-vs-jax-ml-jax" tools: ["eugeneyan-ml-surveys", "jax-ml-jax"] --- # ml-surveys vs jax *GraphCanon updated Jul 12, 2026* ## Verdict Pick ml-surveys when license: ml-surveys is MIT, jax is Apache-2.0; pick jax when license: jax is Apache-2.0, ml-surveys is MIT. [ml-surveys](https://github.com/eugeneyan/ml-surveys) reports 2.9k GitHub stars, 291 forks, and 2 open issues, last pushed Mar 17, 2023. [jax](https://docs.jax.dev) has 36k stars, 3.7k forks, and 2.5k open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [ml-surveys's repository](https://github.com/eugeneyan/ml-surveys) and [jax's repository](https://github.com/jax-ml/jax). | | [ml-surveys](/tools/eugeneyan-ml-surveys.md) | [jax](/tools/jax-ml-jax.md) | | --- | --- | --- | | Tagline | 📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc. | Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more | | Stars | 2,900 | 35,999 | | Forks | 291 | 3,676 | | Open issues | 2 | 2,495 | | Language | - | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Vector Databases, Computer Vision | Vector Databases, Computer Vision, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ml-surveys](/tools/eugeneyan-ml-surveys.md) | [jax](/tools/jax-ml-jax.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 1212d | 0d | | Open issues (now) | 2 | 2.5k | | Owner type | User | Organization | | Full report | [trust report](/tools/eugeneyan-ml-surveys/trust.md) | [trust report](/tools/jax-ml-jax/trust.md) | ## Choose when ### Choose ml-surveys if… - License: ml-surveys is MIT, jax is Apache-2.0. - Tags unique to ml-surveys: reinforcement-learning, embeddings, deep-learning, nlp. - Leaner open-issue backlog (2). ### Choose jax if… - License: jax is Apache-2.0, ml-surveys is MIT. - Tags unique to jax: python, jax. - Also covers Evaluation & Observability. ## When NOT to use ml-surveys - Last GitHub push was 1213 days ago (dormant maintenance, Mar 17, 2023). Validate activity before betting a new project on ml-surveys. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## When NOT to use jax - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## Common questions ### What is the difference between ml-surveys and jax? ml-surveys: 📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.. jax: Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more. See the comparison table for live GitHub stats and shared categories. ### When should I choose ml-surveys over jax? Choose ml-surveys over jax when License: ml-surveys is MIT, jax is Apache-2.0; Tags unique to ml-surveys: reinforcement-learning, embeddings, deep-learning, nlp; Leaner open-issue backlog (2). ### When should I choose jax over ml-surveys? Choose jax over ml-surveys when License: jax is Apache-2.0, ml-surveys is MIT; Tags unique to jax: python, jax; Also covers Evaluation & Observability. ### When should I avoid ml-surveys? Last GitHub push was 1213 days ago (dormant maintenance, Mar 17, 2023). Validate activity before betting a new project on ml-surveys. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### When should I avoid jax? Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### Is ml-surveys or jax more popular on GitHub? jax has more GitHub stars (35,999 vs 2,900). Stars measure visibility, not whether either tool fits your constraints. ### Are ml-surveys and jax open source? Yes - both are open-source projects on GitHub (ml-surveys: MIT, jax: Apache-2.0). ### Where can I find alternatives to ml-surveys or jax? GraphCanon lists graph-backed alternatives at [ml-surveys alternatives](/tools/eugeneyan-ml-surveys/alternatives) and [jax alternatives](/tools/jax-ml-jax/alternatives) ([ml-surveys markdown twin](/tools/eugeneyan-ml-surveys/alternatives.md), [jax markdown twin](/tools/jax-ml-jax/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/eugeneyan-ml-surveys-vs-jax-ml-jax.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ml-surveys or jax? ml-surveys: Dormant. jax: 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 ml-surveys and jax? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ml-surveys trust report](/tools/eugeneyan-ml-surveys/trust); [jax trust report](/tools/jax-ml-jax/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=eugeneyan-ml-surveys`](/api/graphcanon/graph?tool=eugeneyan-ml-surveys) - 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/_