Shepherd Model Gateway – Model-routing gateway for LLM deployments
Shepherd Model Gateway Engine-agnostic, high-performance model-routing gateway for large-scale LLM deployments. Centralizes worker lifecycle management, balances traffic across HTTP/gRPC/OpenAI-compatible backends, and provides enterprise-ready control over history storage, MCP tooling, and privacy-sensitive workflows. API Coverage: OpenAI Chat/Completions/Embeddings, Responses API for agents, Anthropic Messages, and MCP tool execution.
- ▪Shepherd Model Gateway Engine-agnostic, high-performance model-routing gateway for large-scale LLM deployments.
- ▪Centralizes worker lifecycle management, balances traffic across HTTP/gRPC/OpenAI-compatible backends, and provides enterprise-ready control over history storage, MCP tooling, and privacy-sensitive workflows.
- ▪API Coverage: OpenAI Chat/Completions/Embeddings, Responses API for agents, Anthropic Messages, and MCP tool execution.
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Shepherd Model Gateway Engine-agnostic, high-performance model-routing gateway for large-scale LLM deployments. Centralizes worker lifecycle management, balances traffic across HTTP/gRPC/OpenAI-compatible backends, and provides enterprise-ready control over history storage, MCP tooling, and privacy-sensitive workflows. Why SMG? 🚀 Maximize GPU Utilization Cache-aware routing understands your inference engine's KV cache state—whether vLLM, TensorRT-LLM, TokenSpeed, or SGLang—to reuse prefixes and reduce redundant computation. 🔌 One API, Any Backend Route to self-hosted models (vLLM, TensorRT-LLM, TokenSpeed, SGLang) or cloud providers (OpenAI, Anthropic, Gemini, Bedrock, and more) through a single unified endpoint.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.