--- title: "frai vs manifold" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/sebuzdugan-frai-vs-uber-manifold" tools: ["sebuzdugan-frai", "uber-manifold"] --- # frai vs manifold *GraphCanon updated Aug 9, 2026* ## Verdict Pick frai if frai is an open-source toolkit that uses CLI and SDK to scan code for responsible AI development purposes, generating model cards, risk assessments, and evaluations; pick manifold if manifold, developed by Uber, offers ML developers JavaScript-based visualization capabilities to debug and comprehend their models' data processing without the need for model-specific knowledge. [frai](https://frai.cc/) reports 53 GitHub stars, 4 forks, and 0 open issues, last pushed Aug 5, 2026. [manifold](https://github.com/uber/manifold) has 1.7k stars, 116 forks, and 83 open issues, last pushed Feb 5, 2025. Figures are from public GitHub metadata via [frai's repository](https://github.com/sebuzdugan/frai) and [manifold's repository](https://github.com/uber/manifold). | | [frai](/tools/sebuzdugan-frai.md) | [manifold](/tools/uber-manifold.md) | | --- | --- | --- | | Tagline | A toolkit for responsible AI development that generates model cards, risk assessments, and evals via CLI and SDK. | A model-agnostic visual debugging tool for machine learning | | Stars | 53 | 1,673 | | Forks | 4 | 116 | | Open issues | 0 | 83 | | Language | JavaScript | JavaScript | | Adopt for | frai is an open-source toolkit that uses CLI and SDK to scan code for responsible AI development purposes, generating model cards, risk assessments, and evaluations. | Manifold, developed by Uber, offers ML developers JavaScript-based visualization capabilities to debug and comprehend their models' data processing without the need for model-specific knowledge. | | Persona | - | - | | Runtime | - | - | | License | MIT | Manifold is distributed under the Apache-2.0 license, allowing for flexible usage in both commercial and open-source projects. | | Categories | Developer Tools, Evaluation & Observability | Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [frai](/tools/sebuzdugan-frai.md) | [manifold](/tools/uber-manifold.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 3d | 543d | | Open issues (now) | 0 | 83 | | Owner type | User | Organization | | Full report | [trust report](/tools/sebuzdugan-frai/trust.md) | [trust report](/tools/uber-manifold/trust.md) | ## Shared compatibility - **Node.js**: [frai](/tools/sebuzdugan-frai.md) - Node.js runtime; [manifold](/tools/uber-manifold.md) - Node.js runtime ## Decision facts: frai - **Adopt for:** frai is an open-source toolkit that uses CLI and SDK to scan code for responsible AI development purposes, generating model cards, risk assessments, and evaluations. ## Decision facts: manifold - **Pricing:** freemium - Free to use and modify under the Apache-2.0 license terms, Manifold's codebase can be downloaded from its repository without any cost. - **Adopt for:** Manifold, developed by Uber, offers ML developers JavaScript-based visualization capabilities to debug and comprehend their models' data processing without the need for model-specific knowledge. - **License detail:** Manifold is distributed under the Apache-2.0 license, allowing for flexible usage in both commercial and open-source projects. ## Choose when ### Choose frai if… - License: frai is MIT, manifold is Apache-2.0. - Tags unique to frai: ai-compliance, audit, bias, evaluation. - Also covers Evaluation & Observability. - Use when you need to comply with specific safety standards in AI projects using JavaScript framework. ### Choose manifold if… - License: manifold is Apache-2.0, frai is MIT. - Pricing: Free to use and modify under the Apache-2.0 license terms, Manifold's codebase can be downloaded from its repository without any cost.. - Tags unique to manifold: apache-2.0-license, incubation, javascript, visualization. - - When you seek a JavaScript-based tool for visual debugging of machine learning models, irrespective of the model type or framework used ## When NOT to use frai - Avoid if your development environment strictly requires non-JavaScript languages for tool integration. - Not advisable if automated governance and scanning tools are not aligned with organizational compliance policies. ## When NOT to use manifold - - Avoid using Manifold if you are not comfortable working with JavaScript, as it is a primary requirement to integrate this tool into your project environment - - If your development setup strictly avoids npm dependencies or requires isolation from external libraries, Manifold may introduce unnecessary complexity given its specific installation requirements ## Common questions ### What is the difference between frai and manifold? frai: A toolkit for responsible AI development that generates model cards, risk assessments, and evals via CLI and SDK.. manifold: A model-agnostic visual debugging tool for machine learning. See the comparison table for live GitHub stats and shared categories. ### When should I choose frai over manifold? Choose frai over manifold when License: frai is MIT, manifold is Apache-2.0; Tags unique to frai: ai-compliance, audit, bias, evaluation; Also covers Evaluation & Observability; Use when you need to comply with specific safety standards in AI projects using JavaScript framework. ### When should I choose manifold over frai? Choose manifold over frai when License: manifold is Apache-2.0, frai is MIT; Pricing: Free to use and modify under the Apache-2.0 license terms, Manifold's codebase can be downloaded from its repository without any cost.; Tags unique to manifold: apache-2.0-license, incubation, javascript, visualization; - When you seek a JavaScript-based tool for visual debugging of machine learning models, irrespective of the model type or framework used. ### When should I avoid frai? Avoid if your development environment strictly requires non-JavaScript languages for tool integration. Not advisable if automated governance and scanning tools are not aligned with organizational compliance policies. ### When should I avoid manifold? - Avoid using Manifold if you are not comfortable working with JavaScript, as it is a primary requirement to integrate this tool into your project environment - If your development setup strictly avoids npm dependencies or requires isolation from external libraries, Manifold may introduce unnecessary complexity given its specific installation requirements ### Is frai or manifold more popular on GitHub? manifold has more GitHub stars (1,673 vs 53). Stars measure visibility, not whether either tool fits your constraints. ### Are frai and manifold open source? Yes - both are open-source projects on GitHub (frai: MIT, manifold: Apache-2.0). ### Where can I find alternatives to frai or manifold? GraphCanon lists graph-backed alternatives at [frai alternatives](/tools/sebuzdugan-frai/alternatives) and [manifold alternatives](/tools/uber-manifold/alternatives) ([frai markdown twin](/tools/sebuzdugan-frai/alternatives.md), [manifold markdown twin](/tools/uber-manifold/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/sebuzdugan-frai-vs-uber-manifold.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, frai or manifold? frai: Very active. manifold: Dormant. 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 frai and manifold? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [frai trust report](/tools/sebuzdugan-frai/trust); [manifold trust report](/tools/uber-manifold/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=sebuzdugan-frai`](/api/graphcanon/graph?tool=sebuzdugan-frai) - 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/_