{"data":{"slug":"intentee-paddler","name":"paddler","tagline":"Open-source LLM/VLM load balancer and serving platform for self-hosting at scale","github_url":"https://github.com/intentee/paddler","owner":"intentee","repo":"paddler","owner_avatar_url":"https://avatars.githubusercontent.com/u/215040511?v=4","primary_language":"Rust","stars":1663,"forks":97,"topics":["ai","llamacpp","llm","llmops","load-balancer"],"archived":false,"github_pushed_at":"2026-07-19T19:36:21+00:00","maintenance_label":"Steady","stars_delta_30d":21,"url":"https://www.graphcanon.com/tools/intentee-paddler","markdown_url":"https://www.graphcanon.com/tools/intentee-paddler.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/intentee-paddler","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=intentee-paddler","description":"Open-source LLM/VLM load balancer and serving platform for self-hosting LLMs (and VLMs) at scale 🏓🦙 Alternative to projects like llm-d, Docker Model Runner, etc but with less moving parts and simple deployments built around ggml ecosystem. Runs on CPU and GPU.","homepage_url":"https://paddler.intentee.com","license":"Apache-2.0","open_issues":29,"watchers":13,"ai_summary":"Platform for hosting Large Language Models (LLMs) and Visual Language Models (VLMs) with a focus on simplicity in deployment, built around the ggml ecosystem.","readme_excerpt":"## Installation and Quickstart\n\nPaddler is self-contained in a single binary file, so all you need to do to start using it is obtain the `paddler` binary and make it available in your system.\n\nYou can obtain the binary by:\n\n* Option 1: Downloading the latest release from our [GitHub releases](https://github.com/intentee/paddler/releases)\n* Option 2: Or building Paddler from source (MSRV is *1.88.0*)","github_created_at":"2024-04-27T18:07:47+00:00","created_at":"2026-07-07T17:42:48.886817+00:00","updated_at":"2026-08-20T18:01:15.973118+00:00","categories":[{"slug":"inference-serving","name":"Inference & Serving","url":"https://www.graphcanon.com/categories/inference-serving","markdown_url":"https://www.graphcanon.com/categories/inference-serving.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/inference-serving"}],"tags":[{"slug":"ai","name":"ai"},{"slug":"cpu","name":"cpu"},{"slug":"gpu","name":"gpu"},{"slug":"llamacpp","name":"llamacpp"},{"slug":"llm","name":"llm"},{"slug":"llmops","name":"llmops"},{"slug":"load-balancer","name":"load-balancer"}],"trust":{"provenance":{"is_fork":false,"github_id":792847444,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-20T18:01:14.495Z","maintenance":{"label":"Steady","score":60,"methodology":"github_public_v1","releases_90d":4,"days_since_push":31,"last_release_at":"2026-07-19T14:36:31Z","stars_delta_30d":21,"open_issues_delta_30d":3},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:22:00.190Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"mcp":{"source":"repo_scan","observed_at":"2026-08-20T18:01:15.428Z","server_manifest":false},"scan":{"source":"repo_scan","observed_at":"2026-08-20T18:01:15.428Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-20T18:01:15.428Z","managed_saas":false},"languages":{"value":["rust","javascript","typescript"],"source":"github.language+package.json","observed_at":"2026-08-20T18:01:15.428Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-20T18:01:15.428Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-08-20T18:01:15.428Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["Need a platform that simplifies deployments around the ggml ecosystem for self-hosting at scale","Prefer single-binary deployment and less dependency management compared to alternatives like llm-d or Docker Model Runner"],"when_not_to_use":["Require extensive customization options in model serving infrastructure that Paddler's minimalistic design does not support","Seek complex feature sets beyond simple scale-out capabilities, which might be found in more comprehensive platforms"],"source":"enrich:decision_facts","observed_at":"2026-07-12T15:06:45.689Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Paddler offers a streamlined approach to serve LLMs/VLMs with minimal setup complexity, focusing on scaling through simplicity."}]}}