Speed vs. Accuracy: The AI Optimization Game

Discover how TensorRT and Triton Inference Server accelerate AI models through visual comparisons and interactive demos

Optimize Your Model with TensorRT

TensorRT accelerates inference by optimizing your neural network through layer fusion, precision calibration, and kernel optimization.

Neural Network Visualization

Precision Setting

INT8FP16FP32
FP32(32-bit)
Baseline precision, highest accuracy

What is TensorRT?

TensorRT is an SDK for high-performance deep learning inference that optimizes neural networks for production deployment. It applies techniques like layer fusion, precision calibration, and kernel auto-tuning to dramatically reduce latency and memory usage while preserving accuracy.

Layer Fusion

Combines multiple operations into a single optimized kernel

Precision Calibration

Reduces numerical precision while preserving accuracy

Kernel Optimization

Selects the most efficient CUDA implementation for each operation

Performance Comparison

MetricNon-OptimizedOptimizedImprovement
Latency
200ms80ms60% faster
Throughput
5 req/s25 req/s5x higher
GPU Usage
30%85%2.8x better
Power Consumption
120W70W42% less
Accuracy
94%92%2% lower
Model Size
350MB120MB66% smaller

Optimization Pipeline

Before Optimization

U
User
→
M
Slow Model
→
R
Slow Results
200ms inference time

After Optimization

U
User
→
T
Triton
→
TR
TensorRT
→
R
Fast Results
80ms inference time (2.5x faster!)