GTX 1080 Ti vs Quadro RTX 4000

The GTX 1080 Ti delivers higher peak performance than the Quadro RTX 4000: 11.3 TFLOPS FP32 and FP16 compared to 7.1 TFLOPS in both precisions. This advantage translates to faster matrix multiplications in training loops, reducing epochs by up to 37 percent in FP32-bound workloads like scientific simulations. For inference, the extra FP16 throughput supports larger batch sizes without precision loss on older frameworks lacking tensor core optimization.

Memory bandwidth shows GTX 1080 Ti leading at 484 GB/s over 416 GB/s: this permits 16 percent larger batches in memory-limited training, minimizing data loading stalls. The 11 GB VRAM versus 8 GB further enables complex models with high-resolution inputs, such as Stable Diffusion at 1024x1024 without swapping. Quadro RTX 4000's GDDR6 offers lower latency for professional rendering, but Pascal's capacity excels in VRAM-constrained cloud inference.

Power draw differs significantly: 250 W TDP on GTX 1080 Ti versus 160 W demands denser cooling in cloud nodes, potentially raising operational costs. Turing's architecture leverages tensor cores for FP16 inference boosts beyond 7.1 TFLOPS in optimized code, closing the gap in modern deep learning pipelines.

Choose the GTX 1080 Ti for workloads demanding maximum raw compute and VRAM. Its 11.3 TFLOPS FP32 outperforms Quadro RTX 4000's 7.1 TFLOPS by 59 percent, ideal for FP32-heavy scientific computing or legacy ML training. The 11 GB VRAM and 484 GB/s bandwidth handle large datasets in fine-tuning without out-of-memory errors.

At $0.60 per hour, it provides better performance per dollar for bursty cloud tasks where tensor cores add little value.

Select the Quadro RTX 4000 for efficiency-focused professional applications. Its 160 W TDP consumes 36 percent less power than GTX 1080 Ti's 250 W, suiting sustained cloud runs with lower heat. Turing tensor cores accelerate FP16 inference beyond shader limits, benefiting optimized LLM serving.

Availability across five offers at $0.56 per hour ensures reliability, with certified drivers for CAD-integrated ML workflows.