{"data":{"slug":"defilantech-llmkube","name":"LLMKube","tagline":"Kubernetes operator for self-hosted LLM inference across various GPU types","github_url":"https://github.com/defilantech/LLMKube","owner":"defilantech","repo":"LLMKube","owner_avatar_url":"https://avatars.githubusercontent.com/u/69058620?v=4","primary_language":"Go","stars":163,"forks":24,"topics":["ai","apple-silicon","autoscaling","edge-computing","gguf","gpu","homelab","inference","kubernetes","kubernetes-operator","llama-cpp","llm","local-llm","metal","mlx","multi-gpu","nvidia","self-hosted","tgi","vllm"],"archived":false,"github_pushed_at":"2026-07-11T21:51:43+00:00","maintenance_label":"Very active","url":"https://www.graphcanon.com/tools/defilantech-llmkube","markdown_url":"https://www.graphcanon.com/tools/defilantech-llmkube.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/defilantech-llmkube","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=defilantech-llmkube","description":"Kubernetes operator for self-hosted LLM inference across a heterogeneous GPU fleet: NVIDIA CUDA, AMD Vulkan, and Apple Silicon Metal. Runtimes: llama.cpp, vLLM, TGI, mlx-server. Multi-GPU sharding, model caching, OpenAI-compatible endpoints. Apache-2.0, run across homelab and on-prem fleets, actively developed.","homepage_url":"https://llmkube.com","license":"Apache-2.0","open_issues":49,"watchers":1,"ai_summary":"LLMKube is a Kubernetes operator designed to enable the deployment and management of local large language model (LLM) inference services. It supports multiple GPU architectures and provides runtimes like llama.cpp, vLLM, TGI, and mlx-server for efficient multi-GPU sharding and model caching with OpenAI-compatible endpoints.","readme_excerpt":"# Install the CLI\nbrew install defilantech/tap/llmkube\n\n---\n\n# Install the operator on any K8s cluster\nhelm repo add llmkube https://defilantech.github.io/LLMKube\nhelm install llmkube llmkube/llmkube --namespace llmkube-system --create-namespace\n\n---\n\n## License\n\nApache 2.0 — see [LICENSE](LICENSE).","github_created_at":"2025-11-12T22:53:23+00:00","created_at":"2026-07-11T23:11:10.734138+00:00","updated_at":"2026-07-12T04:09:15.676015+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":"apple-silicon","name":"apple-silicon"},{"slug":"gpu","name":"gpu"},{"slug":"kubernetes-operator","name":"kubernetes-operator"},{"slug":"metal","name":"metal"},{"slug":"multi-gpu","name":"multi-gpu"},{"slug":"nvidia","name":"nvidia"},{"slug":"self-hosted","name":"self-hosted"}],"trust":{"provenance":{"is_fork":false,"github_id":1095330682,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-07-11T23:11:18.483Z","maintenance":{"label":"Very active","score":96,"methodology":"github_public_v1","releases_90d":30,"days_since_push":0,"last_release_at":"2026-07-11T21:51:41Z"},"security_summary":{"status":"ok","scanner":"osv@v1","low_count":0,"high_count":0,"last_scan_at":"2026-07-11T23:11:18.849Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-07-12T04:09:15.600Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-07-12T04:09:15.600Z","managed_saas":false},"languages":{"value":["go"],"source":"github.language","observed_at":"2026-07-12T04:09:15.600Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-07-12T04:09:15.600Z"},"license_spdx":{"value":"Apache-2.0","source":"github.license","observed_at":"2026-07-12T04:09:15.600Z"}}}}