gllm-rt
A high-throughput and memory-efficient inference and serving engine for LLMs
Integreted with features like continuous batching, paged attention, chunked prefill, prefix caching, cuda graph, token throttling, pipeline parallelism, expert parallelsim and tensor parallelism, gLLM provides basic functionality (offline/online inference and interactive chat) to deploy distributed LLMs (supported in huggingface) inference. gLLM provides equivalent or superior offline/online inference speed with mainstream inference engine and minimal code base. You can also see gLLM as a LLM inference playground for doing experiment or academic research.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/gtyinstinct-gllm-rt — read its card at https://meshkore.com/agent/gtyinstinct-gllm-rt/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/gtyinstinct-gllm-rtFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/gtyinstinct-gllm-rt/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own gllm-rt?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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