--- title: "parlor vs anything-llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/fikrikarim-parlor-vs-mintplex-labs-anything-llm" tools: ["fikrikarim-parlor", "mintplex-labs-anything-llm"] --- # parlor vs anything-llm *GraphCanon updated Sep 20, 2026* ## Verdict Pick parlor if parlor is an all-in-one multimodal AI solution running entirely on device for real-time voice and vision interactions; pick anything-llm if anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows. [parlor](https://github.com/fikrikarim/parlor) reports 2.1k GitHub stars, 272 forks, and 1 open issues, last pushed Aug 3, 2026. [anything-llm](https://anythingllm.com) has 66k stars, 7.3k forks, and 315 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [parlor's repository](https://github.com/fikrikarim/parlor) and [anything-llm's repository](https://github.com/Mintplex-Labs/anything-llm). | | [parlor](/tools/fikrikarim-parlor.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Tagline | On-device real-time multimodal AI for voice and vision | Self-hosted AI agent experience | | Stars | 2,068 | 66,167 | | Forks | 272 | 7,349 | | Open issues | 1 | 315 | | Language | Python | JavaScript | | Adopt for | Parlor is an all-in-one multimodal AI solution running entirely on device for real-time voice and vision interactions. | anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT License, allowing for free use, modification, and distribution. | | Categories | Computer Vision, Inference & Serving, Speech & Audio | AI Agents, Developer Tools, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [parlor](/tools/fikrikarim-parlor.md) | [anything-llm](/tools/mintplex-labs-anything-llm.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 47d | 0d | | Open issues (now) | 1 | 315 | | Stars delta | +154 (30d) | +1.5k (30d) | | Open issues delta | -8 (30d) | -4 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/fikrikarim-parlor/trust.md) | [trust report](/tools/mintplex-labs-anything-llm/trust.md) | ## Decision facts: parlor - **Adopt for:** Parlor is an all-in-one multimodal AI solution running entirely on device for real-time voice and vision interactions. ## Decision facts: anything-llm - **Pricing:** freemium - Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure. - **Requirements:** Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment. - **Adopt for:** anything-llm is a self-hosted AI agent platform that supports multiple deployment methods, including Docker and cloud services, making it suitable for users who prefer local control over their AI workflows. - **License detail:** MIT License, allowing for free use, modification, and distribution. ## Choose when ### Choose parlor if… - parlor is primarily Python; anything-llm is JavaScript. - License: parlor is Apache-2.0, anything-llm is MIT. - Tags unique to parlor: apple-silicon, gemma, kokoro, litert-lm. - Also covers Computer Vision, Speech & Audio. - Need to run complex, interactive AI locally without relying on cloud services. ### Choose anything-llm if… - anything-llm is primarily JavaScript; parlor is Python. - License: anything-llm is MIT, parlor is Apache-2.0. - Pricing: Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure.. - Requirements: Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment.. - Tags unique to anything-llm: agent-computer, agent-harness, agent-orchestration, agentic-ai. - Also covers AI Agents, Developer Tools. - When you need a local-first AI agent experience that you can fully control and customize. ## When NOT to use parlor - Limited by Python 3.12 requirement and need for specialized hardware such as Apple Silicon. - Insufficient ~3 GB RAM makes it unsuitable for environments with tight memory constraints. ## When NOT to use anything-llm - If you require a cloud-based solution with minimal setup and maintenance, as anything-llm requires self-hosting and local management. - When you need a platform that does not offer extensive deployment flexibility, as anything-llm provides multiple deployment options which might be overwhelming for users seeking simplicity. ## Common questions ### What is the difference between parlor and anything-llm? parlor: On-device real-time multimodal AI for voice and vision. anything-llm: Self-hosted AI agent experience. See the comparison table for live GitHub stats and shared categories. ### When should I choose parlor over anything-llm? Choose parlor over anything-llm when parlor is primarily Python; anything-llm is JavaScript; License: parlor is Apache-2.0, anything-llm is MIT; Tags unique to parlor: apple-silicon, gemma, kokoro, litert-lm; Also covers Computer Vision, Speech & Audio; Need to run complex, interactive AI locally without relying on cloud services. ### When should I choose anything-llm over parlor? Choose anything-llm over parlor when anything-llm is primarily JavaScript; parlor is Python; License: anything-llm is MIT, parlor is Apache-2.0; Pricing: Free to use under the MIT License, but users may incur costs based on their chosen deployment method and infrastructure.; Requirements: Min 4 GB RAM; Requires Docker; Requires a local environment setup or a cloud service account for deployment.; Tags unique to anything-llm: agent-computer, agent-harness, agent-orchestration, agentic-ai; Also covers AI Agents, Developer Tools; When you need a local-first AI agent experience that you can fully control and customize. ### When should I avoid parlor? Limited by Python 3.12 requirement and need for specialized hardware such as Apple Silicon. Insufficient ~3 GB RAM makes it unsuitable for environments with tight memory constraints. ### When should I avoid anything-llm? If you require a cloud-based solution with minimal setup and maintenance, as anything-llm requires self-hosting and local management. When you need a platform that does not offer extensive deployment flexibility, as anything-llm provides multiple deployment options which might be overwhelming for users seeking simplicity. ### Is parlor or anything-llm more popular on GitHub? anything-llm has more GitHub stars (66,167 vs 2,068). Stars measure visibility, not whether either tool fits your constraints. ### Are parlor and anything-llm open source? Yes - both are open-source projects on GitHub (parlor: Apache-2.0, anything-llm: MIT). ### Where can I find alternatives to parlor or anything-llm? GraphCanon lists graph-backed alternatives at [parlor alternatives](/tools/fikrikarim-parlor/alternatives) and [anything-llm alternatives](/tools/mintplex-labs-anything-llm/alternatives) ([parlor markdown twin](/tools/fikrikarim-parlor/alternatives.md), [anything-llm markdown twin](/tools/mintplex-labs-anything-llm/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/fikrikarim-parlor-vs-mintplex-labs-anything-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, parlor or anything-llm? parlor: Steady. anything-llm: 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 parlor and anything-llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [parlor trust report](/tools/fikrikarim-parlor/trust); [anything-llm trust report](/tools/mintplex-labs-anything-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=fikrikarim-parlor`](/api/graphcanon/graph?tool=fikrikarim-parlor) - 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/_