--- title: "ort vs anubis-oss" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/pykeio-ort-vs-uncsoft-anubis-oss" tools: ["pykeio-ort", "uncsoft-anubis-oss"] --- # ort vs anubis-oss *GraphCanon updated Aug 24, 2026* ## Verdict Pick ort if ort accelerates ML inference and training tasks for ONNX models with high-performance Rust operations; pick anubis-oss if anubis-oss, specifically tailored for Apple Silicon devices using Swift, is distinguished by its focus on local large language model evaluation and testing within the macOS environment. [ort](https://ort.pyke.io/) reports 2.5k GitHub stars, 263 forks, and 2 open issues, last pushed Aug 23, 2026. [anubis-oss](https://devpadapp.com/leaderboard.html) has 198 stars, 12 forks, and 4 open issues, last pushed Jun 18, 2026. Figures are from public GitHub metadata via [ort's repository](https://github.com/pykeio/ort) and [anubis-oss's repository](https://github.com/uncSoft/anubis-oss). | | [ort](/tools/pykeio-ort.md) | [anubis-oss](/tools/uncsoft-anubis-oss.md) | | --- | --- | --- | | Tagline | Fast ML inference and training for ONNX models in Rust | Local LLM Testing & Benchmarking for Apple Silicon | | Stars | 2,472 | 198 | | Forks | 263 | 12 | | Open issues | 2 | 4 | | Language | Rust | Swift | | Adopt for | ort accelerates ML inference and training tasks for ONNX models with high-performance Rust operations | Anubis-oss, specifically tailored for Apple Silicon devices using Swift, is distinguished by its focus on local large language model evaluation and testing within the macOS environment. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | GPL-3.0 license ensures that any derivative works related to anubis-oss must also be open source under the same licensing terms. | | Categories | Inference & Serving, Model Training | Evaluation & Observability, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ort](/tools/pykeio-ort.md) | [anubis-oss](/tools/uncsoft-anubis-oss.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 0d | 56d | | Open issues (now) | 2 | 4 | | Stars delta | +56 (30d) | Unknown | | Open issues delta | +1 (30d) | Unknown | | Owner type | Organization | User | | Full report | [trust report](/tools/pykeio-ort/trust.md) | [trust report](/tools/uncsoft-anubis-oss/trust.md) | ## Decision facts: ort - **Adopt for:** ort accelerates ML inference and training tasks for ONNX models with high-performance Rust operations ## Decision facts: anubis-oss - **Pricing:** freemium - The tool is free and open-source with no monetary costs for usage or distribution. - **Requirements:** Min 8 GB RAM - **Adopt for:** Anubis-oss, specifically tailored for Apple Silicon devices using Swift, is distinguished by its focus on local large language model evaluation and testing within the macOS environment. - **License detail:** GPL-3.0 license ensures that any derivative works related to anubis-oss must also be open source under the same licensing terms. ## Choose when ### Choose ort if… - ort is primarily Rust; anubis-oss is Swift. - License: ort is Apache-2.0, anubis-oss is GPL-3.0. - Tags unique to ort: ai, fine-tuning, machine-learning, onnx. - Also covers Model Training. - When your project involves ONNX models that require fast inference times or efficient fine-tuning ### Choose anubis-oss if… - anubis-oss is primarily Swift; ort is Rust. - License: anubis-oss is GPL-3.0, ort is Apache-2.0. - Pricing: The tool is free and open-source with no monetary costs for usage or distribution.. - Requirements: Min 8 GB RAM. - Tags unique to anubis-oss: apple-silicon, benchmarking, gpu, llm. - Also covers Evaluation & Observability. - When developing and evaluating large language models intended to run natively on Apple Silicon hardware. ## When NOT to use ort - When the primary development language is not compatible with Rust bindings - For projects requiring broad model support beyond ONNX, as ort specializes only in ONNX models and does not cover a wide array of formats like some competitors might ## When NOT to use anubis-oss - If your development does not involve Apple Silicon or macOS environments as Anubis-oss is tightly integrated with these platforms. - When preferring a language other than Swift, since Anubis-oss depends on this for its operations. ## Common questions ### What is the difference between ort and anubis-oss? ort: Fast ML inference and training for ONNX models in Rust. anubis-oss: Local LLM Testing & Benchmarking for Apple Silicon. See the comparison table for live GitHub stats and shared categories. ### When should I choose ort over anubis-oss? Choose ort over anubis-oss when ort is primarily Rust; anubis-oss is Swift; License: ort is Apache-2.0, anubis-oss is GPL-3.0; Tags unique to ort: ai, fine-tuning, machine-learning, onnx; Also covers Model Training; When your project involves ONNX models that require fast inference times or efficient fine-tuning. ### When should I choose anubis-oss over ort? Choose anubis-oss over ort when anubis-oss is primarily Swift; ort is Rust; License: anubis-oss is GPL-3.0, ort is Apache-2.0; Pricing: The tool is free and open-source with no monetary costs for usage or distribution.; Requirements: Min 8 GB RAM; Tags unique to anubis-oss: apple-silicon, benchmarking, gpu, llm; Also covers Evaluation & Observability; When developing and evaluating large language models intended to run natively on Apple Silicon hardware. ### When should I avoid ort? When the primary development language is not compatible with Rust bindings For projects requiring broad model support beyond ONNX, as ort specializes only in ONNX models and does not cover a wide array of formats like some competitors might ### When should I avoid anubis-oss? If your development does not involve Apple Silicon or macOS environments as Anubis-oss is tightly integrated with these platforms. When preferring a language other than Swift, since Anubis-oss depends on this for its operations. ### Is ort or anubis-oss more popular on GitHub? ort has more GitHub stars (2,472 vs 198). Stars measure visibility, not whether either tool fits your constraints. ### Are ort and anubis-oss open source? Yes - both are open-source projects on GitHub (ort: Apache-2.0, anubis-oss: GPL-3.0). ### Where can I find alternatives to ort or anubis-oss? GraphCanon lists graph-backed alternatives at [ort alternatives](/tools/pykeio-ort/alternatives) and [anubis-oss alternatives](/tools/uncsoft-anubis-oss/alternatives) ([ort markdown twin](/tools/pykeio-ort/alternatives.md), [anubis-oss markdown twin](/tools/uncsoft-anubis-oss/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/pykeio-ort-vs-uncsoft-anubis-oss.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ort or anubis-oss? ort: Very active. anubis-oss: Steady. 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 ort and anubis-oss? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ort trust report](/tools/pykeio-ort/trust); [anubis-oss trust report](/tools/uncsoft-anubis-oss/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=pykeio-ort`](/api/graphcanon/graph?tool=pykeio-ort) - 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/_