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 32GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 50% higher (864 GB/s vs 576 GB/s), translating directly to faster inference throughput. The Radeon PRO W7900 is $1,604 EUR cheaper than the RTX 5000 Ada Generation.

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

VS
AMD
Radeon PRO W7900
Price
€3,614
VRAM
48 GB GDDR6
Mem. Speed
864 GB/s
FP32 Compute
61.3 TFLOPS
Key Specs Advantage
+50% Bandwidth (864 GB/s vs 576 GB/s)
+50% Memory Bus (384-bit vs 256-bit)
Price
€5,218
VRAM
32 GB GDDR6
Mem. Speed
576 GB/s
FP32 Compute
65.3 TFLOPS
Key Specs Advantage
+108% CUDA Cores (12,800 vs 6,144)
+7% FP32 (TFLOPS) (65.3 TFLOPS vs 61.3 TFLOPS)

Radeon PRO W7900 vs RTX 5000 Ada Generation: In-Depth Breakdown

VRAM: Radeon PRO W7900 vs RTX 5000 Ada Generation

The Radeon PRO W7900 carries 48GB of VRAM versus 32GB on the RTX 5000 Ada Generation. 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 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 576 GB/s on the RTX 5000 Ada Generation, a 50% 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 RTX 5000 Ada Generation delivers 65.3 TFLOPS against 61.3 TFLOPS for the Radeon PRO W7900 — a 7% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX 5000 Ada Generation.

Price & Value

The Radeon PRO W7900 lists from $3,614 EUR, $1,604 EUR less than the RTX 5000 Ada Generation at $5,218 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 5000 Ada Generation?

The Radeon PRO W7900 is the stronger choice for large-model workloads where VRAM is the bottleneck. The RTX 5000 Ada Generation is more economical at $1,604 EUR less, and sufficient if your models fit within its 32GB.

Frequently Asked Questions

Can the Radeon PRO W7900 or RTX 5000 Ada Generation run large language models?

Both can, but the Radeon PRO W7900 (48GB) handles larger models without quantization. The RTX 5000 Ada Generation (32GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Radeon PRO W7900 or the RTX 5000 Ada Generation?

The Radeon PRO W7900 is faster for token generation — its 864 GB/s memory bandwidth vs 576 GB/s on the RTX 5000 Ada Generation is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The RTX 5000 Ada Generation has the advantage at 65.3 TFLOPS vs 61.3 TFLOPS, making training runs proportionally faster than on the Radeon PRO W7900.

Technical Specifications Comparison

Architecture & Cores

SpecificationRadeon PRO W7900RTX 5000 Ada Generation
ArchitectureRDNA 3Ada Lovelace
CUDA Cores (Stream Processors / CUDA Cores)6,14412,800

Memory

SpecificationRadeon PRO W7900RTX 5000 Ada Generation
VRAM Capacity48 GB32 GB
Memory TypeGDDR6GDDR6
Memory Bus384-bit256-bit
Bandwidth864 GB/s576 GB/s

Connectivity & Power

SpecificationRadeon PRO W7900RTX 5000 Ada Generation
InterfacePCIe 4.0 x16PCIe 4.0 x16
TDP295 W250 W
ReleasedNov 2022Nov 2022

Workstation

SpecificationRadeon PRO W7900RTX 5000 Ada Generation
FP32 (TFLOPS)61.3 TFLOPS65.3 TFLOPS
ECCYesYes
NVLinkNoNo
Form factordual-slotdual-slot