GPU Comparison

Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.

Workstation Verdict

The Radeon PRO W7800 has more VRAM (32GB vs 24GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 33% higher (768 GB/s vs 576 GB/s), translating directly to faster inference throughput. The RTX A5000 is $459 USD cheaper than the Radeon PRO W7800.

Maximum Capacity Reached. Remove a model to add another. (2/2)

VS
AMD
Radeon PRO W7800
Price
$2,499 USD
VRAM
32 GB GDDR6
Mem. Speed
576 GB/s
FP32 Compute
45.2 TFLOPS
Key Specs Advantage
+63% FP32 (TFLOPS) (45.2 TFLOPS vs 27.8 TFLOPS)
NVIDIA
RTX A5000
Price
$2,040 USD
VRAM
24 GB GDDR6
Mem. Speed
768 GB/s
FP32 Compute
27.8 TFLOPS
Key Specs Advantage
+113% CUDA Cores (8,192 vs 3,840)
+50% Memory Bus (384-bit vs 256-bit)
+33% Bandwidth (768 GB/s vs 576 GB/s)

Radeon PRO W7800 vs RTX A5000: In-Depth Breakdown

VRAM: Radeon PRO W7800 vs RTX A5000

The Radeon PRO W7800 carries 32GB of VRAM versus 24GB on the RTX A5000. VRAM capacity is the primary constraint for running AI models without quantization — a 70B-parameter model in FP16 requires roughly 140GB, and even smaller models benefit from extra headroom. The 8GB advantage here means the Radeon PRO W7800 can run larger models natively and handle bigger batch sizes in production.

Inference Speed: Memory Bandwidth

Memory bandwidth determines how quickly data is fed to the compute units — it's the main bottleneck for autoregressive inference (token generation in LLMs). The RTX A5000 delivers 768 GB/s versus 576 GB/s on the Radeon PRO W7800, a 33% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX A5000 will produce tokens proportionally faster in bandwidth-bound workloads.

AI Training & Compute

For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The Radeon PRO W7800 delivers 45.2 TFLOPS against 27.8 TFLOPS for the RTX A5000 — a 63% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Radeon PRO W7800.

Price & Value

The RTX A5000 lists from $2,040 USD, $459 USD less than the Radeon PRO W7800 at $2,499 USD. For budget-constrained teams, the savings may outweigh the spec gap — especially if the smaller card covers your typical workload.

Which should you buy: Radeon PRO W7800 or RTX A5000?

These cards suit different priorities. Choose the Radeon PRO W7800 if fitting larger models in VRAM is your constraint. Choose the RTX A5000 if your models already fit and you want faster inference throughput from its higher memory bandwidth.

Frequently Asked Questions

Can the Radeon PRO W7800 or RTX A5000 run large language models?

Both can, but the Radeon PRO W7800 (32GB) handles larger models without quantization. The RTX A5000 (24GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Radeon PRO W7800 or the RTX A5000?

The RTX A5000 is faster for token generation — its 768 GB/s memory bandwidth vs 576 GB/s on the Radeon PRO W7800 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The Radeon PRO W7800 has the advantage at 45.2 TFLOPS vs 27.8 TFLOPS, making training runs proportionally faster than on the RTX A5000.

Technical Specifications Comparison

Architecture & Cores

SpecificationRadeon PRO W7800RTX A5000
ArchitectureRDNA 3Ampere
CUDA Cores (Stream Processors / CUDA Cores)3,8408,192

Memory

SpecificationRadeon PRO W7800RTX A5000
VRAM Capacity32 GB24 GB
Memory TypeGDDR6GDDR6
Memory Bus256-bit384-bit
Bandwidth576 GB/s768 GB/s

Connectivity & Power

SpecificationRadeon PRO W7800RTX A5000
InterfacePCIe 4.0 x16PCIe 4.0 x16
TDP260 W230 W
ReleasedMar 2023Apr 2021

Workstation

SpecificationRadeon PRO W7800RTX A5000
FP32 (TFLOPS)45.2 TFLOPS27.8 TFLOPS
ECCYesYes
NVLinkNoYes
Form factordual-slotdual-slot