GPU Comparison

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

Workstation Verdict

The Radeon PRO W7900 has more VRAM (48GB vs 20GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 35% higher (864 GB/s vs 640 GB/s), translating directly to faster inference throughput. The RTX A4500 is $2,412 EUR cheaper than the Radeon PRO W7900.

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

VS
Price
€3,614
VRAM
48 GB GDDR6
Mem. Speed
864 GB/s
FP32 Compute
61.3 TFLOPS
Key Specs Advantage
+159% FP32 (TFLOPS) (61.3 TFLOPS vs 23.7 TFLOPS)
+35% Bandwidth (864 GB/s vs 640 GB/s)
+20% Memory Bus (384-bit vs 320-bit)
NVIDIA
RTX A4500
Price
€1,202
VRAM
20 GB GDDR6
Mem. Speed
640 GB/s
FP32 Compute
23.7 TFLOPS
Key Specs Advantage
+17% CUDA Cores (7,168 vs 6,144)

Radeon PRO W7900 vs RTX A4500: In-Depth Breakdown

VRAM: Radeon PRO W7900 vs RTX A4500

The Radeon PRO W7900 carries 48GB of VRAM versus 20GB on the RTX A4500. 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 28GB advantage here means the Radeon PRO W7900 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 Radeon PRO W7900 delivers 864 GB/s versus 640 GB/s on the RTX A4500, a 35% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the Radeon PRO W7900 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 W7900 delivers 61.3 TFLOPS against 23.7 TFLOPS for the RTX A4500 — a 159% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Radeon PRO W7900.

Price & Value

The RTX A4500 lists from $1,202 EUR, $2,412 EUR less than the Radeon PRO W7900 at $3,614 EUR. 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 W7900 or RTX A4500?

Choose the Radeon PRO W7900 for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The RTX A4500 is the more budget-friendly option ($2,412 EUR less) — a solid choice if your models fit within its 20GB and inference volume is moderate.

Frequently Asked Questions

Can the Radeon PRO W7900 or RTX A4500 run large language models?

Both can, but the Radeon PRO W7900 (48GB) handles larger models without quantization. The RTX A4500 (20GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Radeon PRO W7900 or the RTX A4500?

The Radeon PRO W7900 is faster for token generation — its 864 GB/s memory bandwidth vs 640 GB/s on the RTX A4500 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The Radeon PRO W7900 has the advantage at 61.3 TFLOPS vs 23.7 TFLOPS, making training runs proportionally faster than on the RTX A4500.

Technical Specifications Comparison

Architecture & Cores

SpecificationRadeon PRO W7900RTX A4500
ArchitectureRDNA 3Ampere
CUDA Cores (Stream Processors / CUDA Cores)6,1447,168

Memory

SpecificationRadeon PRO W7900RTX A4500
VRAM Capacity48 GB20 GB
Memory TypeGDDR6GDDR6
Memory Bus384-bit320-bit
Bandwidth864 GB/s640 GB/s

Connectivity & Power

SpecificationRadeon PRO W7900RTX A4500
InterfacePCIe 4.0 x16PCIe 4.0 x16
TDP295 W200 W
ReleasedNov 2022Oct 2021

Workstation

SpecificationRadeon PRO W7900RTX A4500
FP32 (TFLOPS)61.3 TFLOPS23.7 TFLOPS
ECCYesYes
NVLinkNoYes
Form factordual-slotdual-slot