NVIDIA RTX PRO 4500 Blackwell Server Edition
NVIDIA RTX PRO 4500 Blackwell Server Edition is a single-slot, passive-cooled professional GPU built on the Blackwell architecture, featuring 32GB GDDR7 memory, 165W power consumption, 1.6 FP4 performance in PFLOPS, and support for up to 2 MIG instances. Ideal for enterprise AI inference, visual computing, and high-density data center deployments.
Core Specifications
CompleteSpecifications
| architecture | Blackwell |
| Shape | Single-slot passive cooling (4.4 inch high x 10.5 inch long) |
| TF32 Tensor Core | 203 TFLOPS |
| VRAM | 3 2GB GDDR7 ECC |
| Memory Bandwidth | 800 GB/s |
| Memory bus width | 256-bit |
| CUDA Cores | 10,496 |
| RT Core | 82 fourth-generation, 154 TFLOPS |
| Power Consumption | 200W |
| Location | Enterprise AI Inference, Visual Computing, and High-Density Deployment |
| MIG | Up to 2 instances (1 6GB) |
| FP4 Tensor Core | 1.6 PFLOPS |
| FP8 Tensor Core | 811 TFLOPS |
| FP16/BF16 Tensor Core | 406 TFLOPS |
| FP32 | 51 TFLOPS |
* Sparse mode specifications: Dense performance is half that of sparse specs. Specs sourced from NVIDIA's official product page; actual configuration subject to factory settings.
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NVIDIA RTX PRO 4500 Blackwell Server Edition is a single-slot, passive-cooled professional GPU built on the Blackwell architecture, featuring 32GB GDDR7 memory, 165W power consumption, 1.6 FP4 performance in PFLOPS, and support for up to 2 MIG instances. Ideal for enterprise AI inference, visual computing, and high-density data center deployments.
| architecture | Blackwell |
| Shape | Single-slot passive cooling (4.4 inch high x 10.5 inch long) |
| TF32 Tensor Core | 203 TFLOPS |
| VRAM | 3 2GB GDDR7 ECC |
| Memory Bandwidth | 800 GB/s |
| Memory bus width | 256-bit |
| CUDA Cores | 10,496 |
| RT Core | 82 fourth-generation, 154 TFLOPS |
| Power Consumption | 200W |
| Location | Enterprise AI Inference, Visual Computing, and High-Density Deployment |
| MIG | Up to 2 instances (1 6GB) |
| FP4 Tensor Core | 1.6 PFLOPS |
| FP8 Tensor Core | 811 TFLOPS |
| FP16/BF16 Tensor Core | 406 TFLOPS |
| FP32 | 51 TFLOPS |
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