--- title: "NeumAI vs awesome-llm-apps" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/neumtry-neumai-vs-shubhamsaboo-awesome-llm-apps" tools: ["neumtry-neumai", "shubhamsaboo-awesome-llm-apps"] --- # NeumAI vs awesome-llm-apps *GraphCanon updated Aug 21, 2026* ## Verdict Pick NeumAI if neumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with an open; pick awesome-llm-apps if awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy. [NeumAI](https://neum.ai) reports 867 GitHub stars, 50 forks, and 9 open issues, last pushed Jan 15, 2024. [awesome-llm-apps](https://www.theunwindai.com) has 131k stars, 19k forks, and 13 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [NeumAI's repository](https://github.com/NeumTry/NeumAI) and [awesome-llm-apps's repository](https://github.com/Shubhamsaboo/awesome-llm-apps). | | [NeumAI](/tools/neumtry-neumai.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Tagline | Framework to manage creation and synchronization of vector embeddings at large scale | Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy. | | Stars | 867 | 131,230 | | Forks | 50 | 19,346 | | Open issues | 9 | 13 | | Language | Python | Python | | Adopt for | NeumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with an open | awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. | | Categories | Data & Retrieval, Vector Databases | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [NeumAI](/tools/neumtry-neumai.md) | [awesome-llm-apps](/tools/shubhamsaboo-awesome-llm-apps.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 948d | 4d | | Open issues (now) | 9 | 13 | | Stars delta | +3 (30d) | +14k (30d) | | Open issues delta | 0 (30d) | +6 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/neumtry-neumai/trust.md) | [trust report](/tools/shubhamsaboo-awesome-llm-apps/trust.md) | ## Decision facts: NeumAI - **Pricing:** freemium - Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options. - **Requirements:** Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting. - **Adopt for:** NeumAI stands out in the space of managing large-scale vector embeddings, offering tools tailored for operations such as retrieval-augmented generation (RAG). Users looking to self-host embeddings management with an open ## Decision facts: awesome-llm-apps - **Pricing:** freemium - Free with open-source licensing, but commercial exploitation is allowed. - **Adopt for:** awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python. - **License detail:** The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license. ## Choose when ### Choose NeumAI if… - Pricing: Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options.. - Requirements: Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting.. - Tags unique to NeumAI: ai, data-engineering, database, embeddings. - Also covers Vector Databases. - When you require robust and scalable infrastructure specifically designed for creating and synchronizing vector embeddings at scale. ### Choose awesome-llm-apps if… - Pricing: Free with open-source licensing, but commercial exploitation is allowed.. - Tags unique to awesome-llm-apps: agents, applications, customizable, deployable. - Also covers AI Agents. - When you need quick implementations of various real-world use cases for AI Agents and RAG. ## When NOT to use NeumAI - When your project requires customization beyond what the provided architecture allows, without the support expected from commercial offerings or competitive open-source frameworks. - If your needs are simpler and don't demand large-scale operations, NeumAI’s capabilities focused on handling vast vector sets may be excessive for smaller projects. ## When NOT to use awesome-llm-apps - If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. - When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ## Common questions ### What is the difference between NeumAI and awesome-llm-apps? NeumAI: Framework to manage creation and synchronization of vector embeddings at large scale. awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. See the comparison table for live GitHub stats and shared categories. ### When should I choose NeumAI over awesome-llm-apps? Choose NeumAI over awesome-llm-apps when Pricing: Offers an open-source model under the Apache-2.0 license, potentially featuring a free-tier with premium/support options.; Requirements: Requires Python and compatibility with infrastructure that supports its backend architecture.; Contact their team at founders@tryneum.com for self-hosting.; Tags unique to NeumAI: ai, data-engineering, database, embeddings; Also covers Vector Databases; When you require robust and scalable infrastructure specifically designed for creating and synchronizing vector embeddings at scale. ### When should I choose awesome-llm-apps over NeumAI? Choose awesome-llm-apps over NeumAI when Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; Also covers AI Agents; When you need quick implementations of various real-world use cases for AI Agents and RAG. ### When should I avoid NeumAI? When your project requires customization beyond what the provided architecture allows, without the support expected from commercial offerings or competitive open-source frameworks. If your needs are simpler and don't demand large-scale operations, NeumAI’s capabilities focused on handling vast vector sets may be excessive for smaller projects. ### When should I avoid awesome-llm-apps? If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction. ### Is NeumAI or awesome-llm-apps more popular on GitHub? awesome-llm-apps has more GitHub stars (131,230 vs 867). Stars measure visibility, not whether either tool fits your constraints. ### Are NeumAI and awesome-llm-apps open source? Yes - both are open-source projects on GitHub (NeumAI: Apache-2.0, awesome-llm-apps: Apache-2.0). ### Where can I find alternatives to NeumAI or awesome-llm-apps? GraphCanon lists graph-backed alternatives at [NeumAI alternatives](/tools/neumtry-neumai/alternatives) and [awesome-llm-apps alternatives](/tools/shubhamsaboo-awesome-llm-apps/alternatives) ([NeumAI markdown twin](/tools/neumtry-neumai/alternatives.md), [awesome-llm-apps markdown twin](/tools/shubhamsaboo-awesome-llm-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/neumtry-neumai-vs-shubhamsaboo-awesome-llm-apps.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, NeumAI or awesome-llm-apps? NeumAI: Dormant. awesome-llm-apps: 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 NeumAI and awesome-llm-apps? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [NeumAI trust report](/tools/neumtry-neumai/trust); [awesome-llm-apps trust report](/tools/shubhamsaboo-awesome-llm-apps/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=neumtry-neumai`](/api/graphcanon/graph?tool=neumtry-neumai) - 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/_