GPU Comparison

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

Workstation Verdict

The RTX A4500 has more VRAM (20GB vs 16GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 122% higher (640 GB/s vs 288 GB/s), translating directly to faster inference throughput. The Radeon PRO W7700 is $601 CAD cheaper than the RTX A4500.

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

VS
AMD
Radeon PRO W7700
Price
$1,399 CAD
VRAM
16 GB GDDR6
Mem. Speed
288 GB/s
FP32 Compute
34.6 TFLOPS
Key Specs Advantage
+46% FP32 (TFLOPS) (34.6 TFLOPS vs 23.7 TFLOPS)
NVIDIA
RTX A4500
Price
$2,000 CAD
VRAM
20 GB GDDR6
Mem. Speed
640 GB/s
FP32 Compute
23.7 TFLOPS
Key Specs Advantage
+155% CUDA Cores (7,168 vs 2,816)
+150% Memory Bus (320-bit vs 128-bit)
+122% Bandwidth (640 GB/s vs 288 GB/s)

Radeon PRO W7700 vs RTX A4500: In-Depth Breakdown

VRAM: Radeon PRO W7700 vs RTX A4500

The RTX A4500 carries 20GB of VRAM versus 16GB on the Radeon PRO W7700. 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 4GB advantage here means the RTX A4500 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 A4500 delivers 640 GB/s versus 288 GB/s on the Radeon PRO W7700, a 122% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX A4500 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 W7700 delivers 34.6 TFLOPS against 23.7 TFLOPS for the RTX A4500 — a 46% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Radeon PRO W7700.

Price & Value

The Radeon PRO W7700 lists from $1,399 CAD, $601 CAD less than the RTX A4500 at $2,000 CAD. 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 W7700 or RTX A4500?

The RTX A4500 is the stronger choice for large-model workloads where VRAM is the bottleneck. The Radeon PRO W7700 is more economical at $601 CAD less, and sufficient if your models fit within its 16GB.

Frequently Asked Questions

Can the Radeon PRO W7700 or RTX A4500 run large language models?

Both can, but the RTX A4500 (20GB) handles larger models without quantization. The Radeon PRO W7700 (16GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Radeon PRO W7700 or the RTX A4500?

The RTX A4500 is faster for token generation — its 640 GB/s memory bandwidth vs 288 GB/s on the Radeon PRO W7700 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The Radeon PRO W7700 has the advantage at 34.6 TFLOPS vs 23.7 TFLOPS, making training runs proportionally faster than on the RTX A4500.

Technical Specifications Comparison

Architecture & Cores

SpecificationRadeon PRO W7700RTX A4500
ArchitectureRDNA 3Ampere
CUDA Cores (Stream Processors / CUDA Cores)2,8167,168

Memory

SpecificationRadeon PRO W7700RTX A4500
VRAM Capacity16 GB20 GB
Memory TypeGDDR6GDDR6
Memory Bus128-bit320-bit
Bandwidth288 GB/s640 GB/s

Connectivity & Power

SpecificationRadeon PRO W7700RTX A4500
InterfacePCIe 4.0 x16PCIe 4.0 x16
TDP190 W200 W
ReleasedApr 2023Oct 2021

Workstation

SpecificationRadeon PRO W7700RTX A4500
FP32 (TFLOPS)34.6 TFLOPS23.7 TFLOPS
ECCYesYes
NVLinkNoYes
Form factordual-slotdual-slot