We need to deploy vLLM or Triton for scaling our LLM inference infrastructure today. Which one is currently recommended for production environments under heavy load?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
We need to deploy vLLM or Triton for scaling our LLM inference infrastructure today. Which one is currently recommended for production environments under heavy load?
1 real search · 1 real-search pass
vLLM vs NVIDIA Triton Inference Server production LLM serving 2026 heavy load recommendations benchmarks official documentationGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
vLLM vs NVIDIA Triton Inference Server production LLM serving 2026 heavy load recommendations benchmarks official documentation Google ↗
- vLLM Overview · docs.nvidia.com
- docs.nvidia.com · docs.nvidia.com
- vllm/docs/serving/parallelism_scaling.md at main · vllm-project/vllm · github.com
- server/docs/getting_started/llm.md at main · triton-inference-server/server · github.com
- vLLM Large Scale Serving: DeepSeek @ 2.2k tok/s/H200 with Wide-EP · vllm-project.github.io
- Scaling LLMs with NVIDIA Triton and NVIDIA TensorRT-LLM Using Kubernetes · developer.nvidia.com
- Dynamo-Triton Open-Source Software · developer.nvidia.com