GPU Comparison

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

Workstation Verdict

The RTX A6000 has more VRAM (48GB vs 32GB), 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 A6000 is $2,299 USD cheaper than the Radeon PRO W7800.

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

VS
Price
$2,499 USD
VRAM
32 GB GDDR6
Mem. Speed
576 GB/s
FP32 Compute
45.2 TFLOPS
Key Specs Advantage
+17% FP32 (TFLOPS) (45.2 TFLOPS vs 38.7 TFLOPS)
NVIDIA
RTX A6000
Price
$200 USD
VRAM
48 GB GDDR6
Mem. Speed
768 GB/s
FP32 Compute
38.7 TFLOPS
Key Specs Advantage
+180% CUDA Cores (10,752 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 A6000: In-Depth Breakdown

VRAM: Radeon PRO W7800 vs RTX A6000

The RTX A6000 carries 48GB of VRAM versus 32GB on the Radeon PRO W7800. 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 16GB advantage here means the RTX A6000 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 A6000 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 A6000 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 38.7 TFLOPS for the RTX A6000 — a 17% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Radeon PRO W7800.

Price & Value

The RTX A6000 lists from $200 USD, $2,299 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 A6000?

The RTX A6000 is the stronger choice for large-model workloads where VRAM is the bottleneck. The Radeon PRO W7800 is more economical at $2,299 USD less, and sufficient if your models fit within its 32GB.

Frequently Asked Questions

Can the Radeon PRO W7800 or RTX A6000 run large language models?

Both can, but the RTX A6000 (48GB) handles larger models without quantization. The Radeon PRO W7800 (32GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Radeon PRO W7800 or the RTX A6000?

The RTX A6000 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 38.7 TFLOPS, making training runs proportionally faster than on the RTX A6000.

Technical Specifications Comparison

Architecture & Cores

SpecificationRadeon PRO W7800RTX A6000
ArchitectureRDNA 3Ampere
CUDA Cores (Stream Processors / CUDA Cores)3,84010,752

Memory

SpecificationRadeon PRO W7800RTX A6000
VRAM Capacity32 GB48 GB
Memory TypeGDDR6GDDR6
Memory Bus256-bit384-bit
Bandwidth576 GB/s768 GB/s

Connectivity & Power

SpecificationRadeon PRO W7800RTX A6000
InterfacePCIe 4.0 x16PCIe 4.0 x16
TDP260 W300 W
ReleasedMar 2023Apr 2021

Workstation

SpecificationRadeon PRO W7800RTX A6000
FP32 (TFLOPS)45.2 TFLOPS38.7 TFLOPS
ECCYesYes
NVLinkNoYes
Form factordual-slotdual-slot