--- title: "BrowserAI vs anubis-oss" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/sauravpanda-browserai-vs-uncsoft-anubis-oss" tools: ["sauravpanda-browserai", "uncsoft-anubis-oss"] --- # BrowserAI vs anubis-oss *GraphCanon updated Sep 20, 2026* ## Verdict Pick BrowserAI if browserAI runs various local LLMs directly in your browser using TypeScript; 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. [BrowserAI](https://browserai.dev) reports 1.5k GitHub stars, 136 forks, and 24 open issues, last pushed Jul 21, 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 [BrowserAI's repository](https://github.com/sauravpanda/BrowserAI) and [anubis-oss's repository](https://github.com/uncSoft/anubis-oss). | | [BrowserAI](/tools/sauravpanda-browserai.md) | [anubis-oss](/tools/uncsoft-anubis-oss.md) | | --- | --- | --- | | Tagline | Run local LLMs like llama, deepseek-distill, kokoro and more inside your browser | Local LLM Testing & Benchmarking for Apple Silicon | | Stars | 1,451 | 207 | | Forks | 136 | 15 | | Open issues | 24 | 1 | | Language | TypeScript | Swift | | Adopt for | BrowserAI runs various local LLMs directly in your browser using TypeScript. | 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 | 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, LLM Frameworks | Evaluation & Observability, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [BrowserAI](/tools/sauravpanda-browserai.md) | [anubis-oss](/tools/uncsoft-anubis-oss.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 60d | 15d | | Open issues (now) | 24 | 1 | | Stars delta | +5 (30d) | +9 (30d) | | Open issues delta | 0 (30d) | -3 (30d) | | Full report | [trust report](/tools/sauravpanda-browserai/trust.md) | [trust report](/tools/uncsoft-anubis-oss/trust.md) | ## Decision facts: BrowserAI - **Adopt for:** BrowserAI runs various local LLMs directly in your browser using TypeScript. ## 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 BrowserAI if… - BrowserAI is primarily TypeScript; anubis-oss is Swift. - License: BrowserAI is MIT, anubis-oss is GPL-3.0. - Tags unique to BrowserAI: agents, ai, llm-inference, local. - Also covers LLM Frameworks. - You need to run local models like llama, deepseek-distill, kokoro inside the browser environment. ### Choose anubis-oss if… - anubis-oss is primarily Swift; BrowserAI is TypeScript. - License: anubis-oss is GPL-3.0, BrowserAI 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 BrowserAI - You require a server-based solution instead of in-browser execution for LLMs. - The project involves extensive training tasks that are unsuitable for browser environments. ## 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 BrowserAI and anubis-oss? BrowserAI: Run local LLMs like llama, deepseek-distill, kokoro and more inside your browser. anubis-oss: Local LLM Testing & Benchmarking for Apple Silicon. See the comparison table for live GitHub stats and shared categories. ### When should I choose BrowserAI over anubis-oss? Choose BrowserAI over anubis-oss when BrowserAI is primarily TypeScript; anubis-oss is Swift; License: BrowserAI is MIT, anubis-oss is GPL-3.0; Tags unique to BrowserAI: agents, ai, llm-inference, local; Also covers LLM Frameworks; You need to run local models like llama, deepseek-distill, kokoro inside the browser environment. ### When should I choose anubis-oss over BrowserAI? Choose anubis-oss over BrowserAI when anubis-oss is primarily Swift; BrowserAI is TypeScript; License: anubis-oss is GPL-3.0, BrowserAI 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 BrowserAI? You require a server-based solution instead of in-browser execution for LLMs. The project involves extensive training tasks that are unsuitable for browser environments. ### 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 BrowserAI or anubis-oss more popular on GitHub? BrowserAI has more GitHub stars (1,451 vs 207). Stars measure visibility, not whether either tool fits your constraints. ### Are BrowserAI and anubis-oss open source? Yes - both are open-source projects on GitHub (BrowserAI: MIT, anubis-oss: GPL-3.0). ### Where can I find alternatives to BrowserAI or anubis-oss? GraphCanon lists graph-backed alternatives at [BrowserAI alternatives](/tools/sauravpanda-browserai/alternatives) and [anubis-oss alternatives](/tools/uncsoft-anubis-oss/alternatives) ([BrowserAI markdown twin](/tools/sauravpanda-browserai/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/sauravpanda-browserai-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, BrowserAI or anubis-oss? BrowserAI: Steady. 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 BrowserAI and anubis-oss? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [BrowserAI trust report](/tools/sauravpanda-browserai/trust); [anubis-oss trust report](/tools/uncsoft-anubis-oss/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=sauravpanda-browserai`](/api/graphcanon/graph?tool=sauravpanda-browserai) - 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/_