--- title: "anything-llm vs awesome-ai-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/mintplex-labs-anything-llm-vs-rohitg00-awesome-ai-apps" tools: ["mintplex-labs-anything-llm", "rohitg00-awesome-ai-apps"] --- # anything-llm vs awesome-ai-apps *GraphCanon updated Jul 15, 2026* ## Verdict Pick anything-llm when anything-llm is primarily JavaScript; awesome-ai-apps is HTML; pick awesome-ai-apps when awesome-ai-apps is primarily HTML; anything-llm is JavaScript. [anything-llm](https://anythingllm.com) reports 63k GitHub stars, 6.9k forks, and 320 open issues, last pushed Jul 11, 2026. [awesome-ai-apps](https://agenstskills.com) has 803 stars, 172 forks, and 29 open issues, last pushed Feb 10, 2026. Figures are from public GitHub metadata via [anything-llm's repository](https://github.com/Mintplex-Labs/anything-llm) and [awesome-ai-apps's repository](https://github.com/rohitg00/awesome-ai-apps). | | [anything-llm](/tools/mintplex-labs-anything-llm.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Tagline | Self-hosted agent experience with deployment scripts for multiple environments | A curated collection of awesome AI Agents and LLM Apps built with multiple tech stacks, showcasing real-world implementations using OpenAI, Gemini, local models, and various AI frameworks. | | Stars | 63,100 | 803 | | Forks | 6,907 | 172 | | Open issues | 320 | 29 | | Language | JavaScript | HTML | | Adopt for | Self-hosted AI agent experience with robust deployment scripts across multiple environments. | - | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Inference & Serving | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [anything-llm](/tools/mintplex-labs-anything-llm.md) | [awesome-ai-apps](/tools/rohitg00-awesome-ai-apps.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 154d | | Open issues (now) | 320 | 29 | | Owner type | Organization | User | | Full report | [trust report](/tools/mintplex-labs-anything-llm/trust.md) | [trust report](/tools/rohitg00-awesome-ai-apps/trust.md) | ## Decision facts: anything-llm - **Adopt for:** Self-hosted AI agent experience with robust deployment scripts across multiple environments. ## Choose when ### Choose anything-llm if… - anything-llm is primarily JavaScript; awesome-ai-apps is HTML. - License: anything-llm is MIT, awesome-ai-apps is Apache-2.0. - Tags unique to anything-llm: agent-computer, agent-harness, agentic-ai, local-ai. - Also covers Inference & Serving. - When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more. ### Choose awesome-ai-apps if… - awesome-ai-apps is primarily HTML; anything-llm is JavaScript. - License: awesome-ai-apps is Apache-2.0, anything-llm is MIT. - Tags unique to awesome-ai-apps: agents, ai, apps, automation. - Also covers LLM Frameworks. ## When NOT to use anything-llm - Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments. - Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods. ## When NOT to use awesome-ai-apps - Last GitHub push was 154 days ago (slowing maintenance, Feb 10, 2026). Validate activity before betting a new project on awesome-ai-apps. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between anything-llm and awesome-ai-apps? anything-llm: Self-hosted agent experience with deployment scripts for multiple environments. awesome-ai-apps: A curated collection of awesome AI Agents and LLM Apps built with multiple tech stacks, showcasing real-world implementations using OpenAI, Gemini, local models, and various AI frameworks.. See the comparison table for live GitHub stats and shared categories. ### When should I choose anything-llm over awesome-ai-apps? Choose anything-llm over awesome-ai-apps when anything-llm is primarily JavaScript; awesome-ai-apps is HTML; License: anything-llm is MIT, awesome-ai-apps is Apache-2.0; Tags unique to anything-llm: agent-computer, agent-harness, agentic-ai, local-ai; Also covers Inference & Serving; When you need flexibility in deploying your AI agents on various cloud platforms like AWS, GCP, Digital Ocean, and more. ### When should I choose awesome-ai-apps over anything-llm? Choose awesome-ai-apps over anything-llm when awesome-ai-apps is primarily HTML; anything-llm is JavaScript; License: awesome-ai-apps is Apache-2.0, anything-llm is MIT; Tags unique to awesome-ai-apps: agents, ai, apps, automation; Also covers LLM Frameworks. ### When should I avoid anything-llm? Avoid if you require an agent without additional setup or prefer SaaS solutions over self-managed deployments. Not suitable for users who are looking for no-code alternatives as setting up AnythingLLM might necessitate some coding knowledge despite offering multiple scripts and methods. ### When should I avoid awesome-ai-apps? Last GitHub push was 154 days ago (slowing maintenance, Feb 10, 2026). Validate activity before betting a new project on awesome-ai-apps. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is anything-llm or awesome-ai-apps more popular on GitHub? anything-llm has more GitHub stars (63,100 vs 803). Stars measure visibility, not whether either tool fits your constraints. ### Are anything-llm and awesome-ai-apps open source? Yes - both are open-source projects on GitHub (anything-llm: MIT, awesome-ai-apps: Apache-2.0). ### Where can I find alternatives to anything-llm or awesome-ai-apps? GraphCanon lists graph-backed alternatives at [anything-llm alternatives](/tools/mintplex-labs-anything-llm/alternatives) and [awesome-ai-apps alternatives](/tools/rohitg00-awesome-ai-apps/alternatives) ([anything-llm markdown twin](/tools/mintplex-labs-anything-llm/alternatives.md), [awesome-ai-apps markdown twin](/tools/rohitg00-awesome-ai-apps/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/mintplex-labs-anything-llm-vs-rohitg00-awesome-ai-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, anything-llm or awesome-ai-apps? anything-llm: Very active. awesome-ai-apps: Slowing. 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 anything-llm and awesome-ai-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [anything-llm trust report](/tools/mintplex-labs-anything-llm/trust); [awesome-ai-apps trust report](/tools/rohitg00-awesome-ai-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=mintplex-labs-anything-llm`](/api/graphcanon/graph?tool=mintplex-labs-anything-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/_