Text decision tree
Match NIM, Dynamo-Triton, TensorRT-LLM and Dynamo to your model packaging, optimization and serving needs.
Adapted from Chapter 91 of Decision Trees: Frameworks for Technology Choices. Sources reviewed 2026-11-05.
START
Q0 Supported packaged model fits deployment needs?
YES -> NVIDIA NIM candidate. Check the exact model, hardware and service interface. Then Q1.
NO -> Otherwise own the model packaging and choose a suitable inference engine. Then Q1.
Q1 Need one server across multiple model frameworks?
YES -> Dynamo-Triton / Triton. Multi-framework serving and model management. Then Q2.
NO -> Otherwise keep the simpler runtime already selected. Then Q2.
Q2 GPU bottleneck justifies optimization ownership?
YES -> TensorRT-LLM candidate. Benchmark supported models on target hardware. Then Q3.
NO -> Otherwise retain the existing engine and benchmark before adding optimization work. Then Q3.
Q3 Need distributed LLM routing or disaggregation?
YES -> NVIDIA Dynamo. Orchestrate the chosen supported engine. Then Q4.
NO -> Otherwise keep the simpler serving topology. Then Q4.
Q4 Commercial support or closed-network requirements?
YES -> Validate the exact product offering. Check license, artifacts, updates and support scope. Then Q5.
NO -> Otherwise verify the selected licenses and take explicit ownership of operations. Then Q5.
Q5 Model, hardware, quality and cost checks pass?
YES -> Adopt the measured combination. Use the smallest passing stack. Then END.
NO -> Otherwise rework the failed layer and evaluate again. Then STOP.
END: Adopt the smallest combination that passes the workload evaluation. These products are layers, not four mutually exclusive alternatives.
AI-generated chapter illustration
BookWriter-generated chapter 91 illustration
This AI-generated illustration gives a visual overview. It can simplify labels or imply connections that do not preserve every decision. For exact branches, prerequisites and stop conditions, follow the video graph and the text tree above.
Reference links
- Validated Kubernetes runtime for NVIDIA Dynamo — 2026-10-30.
- TensorRT multi-device integration in Dynamo-Triton — 2026-09-21.
- Full-stack NIM optimizations for Nemotron 3 Ultra — 2026-09-10.