Why this fit
Teams evaluating AI models, assistants and generative workflows, particularly container platforms and teams that run software on their own infrastructure — free to start.
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llmkube.com
LLMKube
Kubernetes operator for self-hosted LLM inference with pluggable runtimes (llama.cpp, vLLM, TGI, Ollama, vllm-swift), multi-GPU sharding, NV...
Checked Oct 27, 2026Evidence completeness: evidence — not yet recorded: repository signal
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Kubernetes operator for self-hosted LLM inference with pluggable runtimes (llama.cpp, vLLM, TGI, Ollama, vllm-swift), multi-GPU sharding, NVIDIA CUDA + Apple Silicon Metal support, and OpenAI-compatible API. (Source Code) Apache-2.0 Go/Docker/K8S
Best for
Teams evaluating AI models, assistants and generative workflows, particularly container platforms and teams that run software on their own infrastructure — free to start.
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
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Evidence summary
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
Catalogue confidence
Catalogue data checked Oct 27, 2026.
Oryxen catalogue record without GitHub-backed evidence.
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- Listed in active catalogue
- Freshness
- Catalogue updated Oct 27, 2026
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- Oryxen catalogue record
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