--- title: "awesome-local-llm vs anubis-oss" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/rafska-awesome-local-llm-vs-uncsoft-anubis-oss" tools: ["rafska-awesome-local-llm", "uncsoft-anubis-oss"] --- # awesome-local-llm vs anubis-oss *GraphCanon updated Sep 20, 2026* ## Verdict Pick awesome-local-llm if awesome-local-llm is a curated list of resources for the local operation of large language models; 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. [awesome-local-llm](https://github.com/rafska/awesome-local-llm) reports 2.9k GitHub stars, 388 forks, and 169 open issues, last pushed Sep 13, 2026. [anubis-oss](https://devpadapp.com/leaderboard.html) has 207 stars, 15 forks, and 1 open issues, last pushed Sep 5, 2026. Figures are from public GitHub metadata via [awesome-local-llm's repository](https://github.com/rafska/awesome-local-llm) and [anubis-oss's repository](https://github.com/uncSoft/anubis-oss). | | [awesome-local-llm](/tools/rafska-awesome-local-llm.md) | [anubis-oss](/tools/uncsoft-anubis-oss.md) | | --- | --- | --- | | Tagline | Resources for running LLMs locally | Local LLM Testing & Benchmarking for Apple Silicon | | Stars | 2,869 | 207 | | Forks | 388 | 15 | | Open issues | 169 | 1 | | Language | - | Swift | | Adopt for | awesome-local-llm is a curated list of resources for the local operation of large language models. | 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 | MIT License | 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 | Evaluation & Observability, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [awesome-local-llm](/tools/rafska-awesome-local-llm.md) | [anubis-oss](/tools/uncsoft-anubis-oss.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 6d | 15d | | Open issues (now) | 169 | 1 | | Stars delta | +351 (30d) | +9 (30d) | | Open issues delta | +40 (30d) | -3 (30d) | | Full report | [trust report](/tools/rafska-awesome-local-llm/trust.md) | [trust report](/tools/uncsoft-anubis-oss/trust.md) | ## Decision facts: awesome-local-llm - **Pricing:** freemium - The list itself is free and open-source under the MIT license. - **Requirements:** Technical skill in setting up a self-hosted large language model environment is necessary - **Adopt for:** awesome-local-llm is a curated list of resources for the local operation of large language models. - **License detail:** MIT License ## 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 awesome-local-llm if… - License: awesome-local-llm is MIT, anubis-oss is GPL-3.0. - Pricing: The list itself is free and open-source under the MIT license.. - Requirements: Technical skill in setting up a self-hosted large language model environment is necessary. - Tags unique to awesome-local-llm: ai, awesome-list, local-ai, self-hosted. - - If you require extensive documentation and resources for setting up and running LLMs on your own hardware, this tool provides a comprehensive list of options ### Choose anubis-oss if… - License: anubis-oss is GPL-3.0, awesome-local-llm is MIT. - 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, inference. - Also covers Evaluation & Observability. - When developing and evaluating large language models intended to run natively on Apple Silicon hardware. ## When NOT to use awesome-local-llm - - Avoid if you seek direct tools rather than a curated list; awesome-local-llm does not provide the actual software but guidance and links - - Not suitable for users who prefer ready-to-use solutions without needing additional configuration, as it requires self-hosting expertise to utilize its resources ## 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 awesome-local-llm and anubis-oss? awesome-local-llm: Resources for running LLMs locally. anubis-oss: Local LLM Testing & Benchmarking for Apple Silicon. See the comparison table for live GitHub stats and shared categories. ### When should I choose awesome-local-llm over anubis-oss? Choose awesome-local-llm over anubis-oss when License: awesome-local-llm is MIT, anubis-oss is GPL-3.0; Pricing: The list itself is free and open-source under the MIT license.; Requirements: Technical skill in setting up a self-hosted large language model environment is necessary; Tags unique to awesome-local-llm: ai, awesome-list, local-ai, self-hosted; - If you require extensive documentation and resources for setting up and running LLMs on your own hardware, this tool provides a comprehensive list of options. ### When should I choose anubis-oss over awesome-local-llm? Choose anubis-oss over awesome-local-llm when License: anubis-oss is GPL-3.0, awesome-local-llm is MIT; 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, inference; Also covers Evaluation & Observability; When developing and evaluating large language models intended to run natively on Apple Silicon hardware. ### When should I avoid awesome-local-llm? - Avoid if you seek direct tools rather than a curated list; awesome-local-llm does not provide the actual software but guidance and links - Not suitable for users who prefer ready-to-use solutions without needing additional configuration, as it requires self-hosting expertise to utilize its resources ### 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 awesome-local-llm or anubis-oss more popular on GitHub? awesome-local-llm has more GitHub stars (2,869 vs 207). Stars measure visibility, not whether either tool fits your constraints. ### Are awesome-local-llm and anubis-oss open source? Yes - both are open-source projects on GitHub (awesome-local-llm: MIT, anubis-oss: GPL-3.0). ### Where can I find alternatives to awesome-local-llm or anubis-oss? GraphCanon lists graph-backed alternatives at [awesome-local-llm alternatives](/tools/rafska-awesome-local-llm/alternatives) and [anubis-oss alternatives](/tools/uncsoft-anubis-oss/alternatives) ([awesome-local-llm markdown twin](/tools/rafska-awesome-local-llm/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/rafska-awesome-local-llm-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, awesome-local-llm or anubis-oss? awesome-local-llm: Very active. anubis-oss: 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 awesome-local-llm and anubis-oss? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [awesome-local-llm trust report](/tools/rafska-awesome-local-llm/trust); [anubis-oss trust report](/tools/uncsoft-anubis-oss/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=rafska-awesome-local-llm`](/api/graphcanon/graph?tool=rafska-awesome-local-llm) - 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/_