ChatGPT SearchSep 22, 2026
llm-d/disaggregated inference focuses specifically on highly variable agent workloads.
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Data as of Oct 14, 2026Based on 6,708 AI responses
Reviewed by Dimitry Apollonsky
AI summary
llm-d is an open-source, Kubernetes-native stack for distributed LLM inference that runs models like vLLM and SGLang across a cluster.
<1%
of 6,708 answers across llm-d’s markets · since Jul 5
The market map
MLOps and Inference Serving PlatformsMentioned in
Question: We need a chip compiler or runtime optimized for bursty agent workloads. Which companies are building this?
ChatGPT SearchSep 22, 2026
llm-d/disaggregated inference focuses specifically on highly variable agent workloads.
Share of answers in MLOps and Inference Serving Platforms each week · 927 answers since Jul 5
Each engine’s share of its own answers across llm-d’s markets · since Jul 5
Where llm-d ranks in AI
Question: Which open-source AI infrastructure startups are most useful for startups that need flexibility and low cost?
ChatGPT SearchJun 16, 2026
llm-d (Red Hat ecosystem project) - Kubernetes-native distributed inference
llm-d.ai 0%Other sites 100%
Excerpts where llm-d appeared in the AI's answer
llm-d (Red Hat ecosystem project) - Kubernetes-native distributed inference
Excerpts where llm-d appeared in the AI's answer
llm-d/disaggregated inference focuses specifically on highly variable agent workloads.
