Agentic AI Reference Architecture

Model Serving · Model asset

TF32 Inference Engine

Model assetModel ServingModelsarc:TF32InferenceEngine

A model execution configuration using the TensorFloat-32 format (FP32 exponent range with a 10-bit mantissa) that gives near-FP32 accuracy with FP16-like speed and no quantization workflow.

Responsibility. Accelerates inference on Ampere-or-newer GPUs without calibration or explicit quantization.

Also known as: TensorFloat-32

Variant of Optimized Inference Engine abstract

When to choose. Choose when targeting Ampere-or-newer hardware exclusively and near-FP32 accuracy is required without a quantization workflow.

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Direct neighbourhood (hover for relationship types)

Relationships

alternative to variability

Quantitative guidance

As stated by the sources; verify before use.

Classification

Technologies
NVIDIA Ampere Tensor Cores
Quality attributes
Functional suitability: correctness and validity (ISO/IEC 25010 | NIST AI RMF: valid)Maintainability (ISO/IEC 25010)

Sources

  1. Ch7.4: T. Nguyen, "TensorRT-LLM Fundamentals and Quantization," in Mastering Agentic AI Systems: Guide for the NVIDIA NCP-AAI Exam, 1st ed. 2026, ch. 7.4. ISBN: 9798244538229.
  2. Ref7.01: NVIDIA, "Best practices," NVIDIA TensorRT Documentation. Accessed: Sep. 27, 2026. [Online]. Available: https://docs.nvidia.com/deeplearning/tensorrt/latest/performance/best-practices.html