--- title: "agenta vs paddler" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agenta-ai-agenta-vs-intentee-paddler" tools: ["agenta-ai-agenta", "intentee-paddler"] --- # agenta vs paddler Neutral, constraint-first comparison with live GitHub stats. | | [agenta](/tools/agenta-ai-agenta.md) | [paddler](/tools/intentee-paddler.md) | | --- | --- | --- | | Tagline | The open-source LLMOps platform | Open-source LLM load balancer and serving platform | | Stars | 4,275 | 1,627 | | Forks | 562 | 89 | | Open issues | 161 | 25 | | Language | TypeScript | Rust | | Adopt for | Agента is an open-source LLMOps platform that provides comprehensive capabilities for prompt management, evaluation, and observability of LLM applications. | Paddler is a self-hosting platform built in Rust for managing inference and deployment of Language and Vision Models (LLMs/VLMs) on private infrastructure. It offers features like dynamic agent addition, request handling | | Persona | - | - | | Runtime | - | - | | License | The software is distributed under the MIT license, making it free for use and modification. | Apache-2.0 | | Categories | Evaluation & Observability, LLM Frameworks | Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agenta](/tools/agenta-ai-agenta.md) | [paddler](/tools/intentee-paddler.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 161 | 25 | | Security scan | No lockfile | No criticals | | Full report | [trust report](/tools/agenta-ai-agenta/trust.md) | [trust report](/tools/intentee-paddler/trust.md) | **Typed relationship:** agenta _(alternative)_ paddler Both Paddler and Agenta offer platforms for deploying, managing, and scaling LLMs on self-hosted infrastructure. They provide similar functionalities with unique approaches to solving the same challenge. ## Decision facts: agenta - **Adopt for:** Agента is an open-source LLMOps platform that provides comprehensive capabilities for prompt management, evaluation, and observability of LLM applications. - **License detail:** The software is distributed under the MIT license, making it free for use and modification. ## Decision facts: paddler - **Requirements:** Min 8 GB RAM; Requires a Rust toolchain with MSRV of at least 1.88.0 for building from source. - **Adopt for:** Paddler is a self-hosting platform built in Rust for managing inference and deployment of Language and Vision Models (LLMs/VLMs) on private infrastructure. It offers features like dynamic agent addition, request handling ## Choose when ### Choose agenta if… - agenta is primarily TypeScript; paddler is Rust. - License: agenta is Other, paddler is Apache-2.0. - Both Paddler and Agenta offer platforms for deploying, managing, and scaling LLMs on self-hosted infrastructure. They provide similar functionalities with unique approaches to solving the same challenge. - Tags unique to agenta: evaluation, agents, prompt-management, llm-observability. - Also covers Evaluation & Observability, LLM Frameworks. - - When you need a unified platform for managing prompts, evaluating model performance, and monitoring LLM applications. ### Choose paddler if… - paddler is primarily Rust; agenta is TypeScript. - License: paddler is Apache-2.0, agenta is Other. - Requirements: Min 8 GB RAM; Requires a Rust toolchain with MSRV of at least 1.88.0 for building from source.. - Both Paddler and Agenta offer platforms for deploying, managing, and scaling LLMs on self-hosted infrastructure. They provide similar functionalities with unique approaches to solving the same challenge. - Tags unique to paddler: llmops, ggml ecosystem, deployment, ai. - Also covers Inference & Serving. - paddler ships Docker support for self-hosted deployment. - - When you need to deploy LLM and VLM models at scale with precise control over your own hardware and software environment. ## When NOT to use agenta - - If your project already has a robust set of isolated tools for prompt engineering, evaluation, or observability that you do not wish to unify under one platform. - - In cases where open-source licensing conflicts with your project's requirements or policies, as Agenta is MIT-licensed. ## When NOT to use paddler - - If you prefer platforms with a larger community base or extensive third-party integrations. Paddler may not offer the depth of support for specific use cases as more established competitors might. - - For those looking for extensive pre-built model integration and automation tools, since Paddler focuses on minimalistic setup around ggml ecosystem. ## Common questions ### What is the difference between agenta and paddler? agenta: The open-source LLMOps platform. paddler: Open-source LLM load balancer and serving platform. See the comparison table for live GitHub stats and shared categories. ### When should I choose agenta over paddler? Choose agenta over paddler when agenta is primarily TypeScript; paddler is Rust; License: agenta is Other, paddler is Apache-2.0; Both Paddler and Agenta offer platforms for deploying, managing, and scaling LLMs on self-hosted infrastructure. They provide similar functionalities with unique approaches to solving the same challenge; Tags unique to agenta: evaluation, agents, prompt-management, llm-observability; Also covers Evaluation & Observability, LLM Frameworks; - When you need a unified platform for managing prompts, evaluating model performance, and monitoring LLM applications. ### When should I choose paddler over agenta? Choose paddler over agenta when paddler is primarily Rust; agenta is TypeScript; License: paddler is Apache-2.0, agenta is Other; Requirements: Min 8 GB RAM; Requires a Rust toolchain with MSRV of at least 1.88.0 for building from source.; Both Paddler and Agenta offer platforms for deploying, managing, and scaling LLMs on self-hosted infrastructure. They provide similar functionalities with unique approaches to solving the same challenge; Tags unique to paddler: llmops, ggml ecosystem, deployment, ai; Also covers Inference & Serving; paddler ships Docker support for self-hosted deployment; - When you need to deploy LLM and VLM models at scale with precise control over your own hardware and software environment. ### When should I avoid agenta? - If your project already has a robust set of isolated tools for prompt engineering, evaluation, or observability that you do not wish to unify under one platform. - In cases where open-source licensing conflicts with your project's requirements or policies, as Agenta is MIT-licensed. ### When should I avoid paddler? - If you prefer platforms with a larger community base or extensive third-party integrations. Paddler may not offer the depth of support for specific use cases as more established competitors might. - For those looking for extensive pre-built model integration and automation tools, since Paddler focuses on minimalistic setup around ggml ecosystem. ### Is agenta or paddler more popular on GitHub? agenta has more GitHub stars (4,275 vs 1,627). Stars measure visibility, not whether either tool fits your constraints. ### Are agenta and paddler open source? Yes - both are open-source projects on GitHub (agenta: Other, paddler: Apache-2.0). ### Where can I find alternatives to agenta or paddler? GraphCanon lists graph-backed alternatives at /tools/agenta-ai-agenta/alternatives and /tools/intentee-paddler/alternatives (/tools/agenta-ai-agenta/alternatives.md, /tools/intentee-paddler/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 /compare/agenta-ai-agenta-vs-intentee-paddler.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agenta or paddler? agenta: Very active. paddler: 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 agenta and paddler? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agenta: /tools/agenta-ai-agenta/trust; paddler: /tools/intentee-paddler/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agenta-ai-agenta`](/api/graphcanon/graph?tool=agenta-ai-agenta) - 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/_