GPU Comparison

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

Workstation Verdict

The RTX PRO 4000 Blackwell has more VRAM (24GB vs 8GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 133% higher (672 GB/s vs 288 GB/s), translating directly to faster inference throughput. The RTX PRO 4000 Blackwell is $632 GBP cheaper than the Radeon PRO W7600.

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

VS
Price
£2,412
VRAM
8 GB GDDR6
Mem. Speed
288 GB/s
FP32 Compute
21.5 TFLOPS
Key Specs Advantage

Comparable or lower specs

NVIDIA
RTX PRO 4000 Blackwell
Price
£1,780
VRAM
24 GB GDDR7
Mem. Speed
672 GB/s
FP32 Compute
46 TFLOPS
Key Specs Advantage
+338% CUDA Cores (8,960 vs 2,048)
+133% Bandwidth (672 GB/s vs 288 GB/s)
+114% FP32 (TFLOPS) (46 TFLOPS vs 21.5 TFLOPS)

Radeon PRO W7600 vs RTX PRO 4000 Blackwell: In-Depth Breakdown

VRAM: Radeon PRO W7600 vs RTX PRO 4000 Blackwell

The RTX PRO 4000 Blackwell carries 24GB of VRAM versus 8GB on the Radeon PRO W7600. 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 PRO 4000 Blackwell 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 PRO 4000 Blackwell delivers 672 GB/s versus 288 GB/s on the Radeon PRO W7600, a 133% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX PRO 4000 Blackwell 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 PRO 4000 Blackwell delivers 46 TFLOPS against 21.5 TFLOPS for the Radeon PRO W7600 — a 114% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX PRO 4000 Blackwell.

Price & Value

The RTX PRO 4000 Blackwell lists from $1,780 GBP, $632 GBP less than the Radeon PRO W7600 at $2,412 GBP. 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 W7600 or RTX PRO 4000 Blackwell?

The RTX PRO 4000 Blackwell is the stronger choice for large-model workloads where VRAM is the bottleneck. The Radeon PRO W7600 is more economical at $632 GBP less, and sufficient if your models fit within its 8GB.

Frequently Asked Questions

Can the Radeon PRO W7600 or RTX PRO 4000 Blackwell run large language models?

Both can, but the RTX PRO 4000 Blackwell (24GB) handles larger models without quantization. The Radeon PRO W7600 (8GB) works well for smaller or heavily quantized models.

Which is faster for LLM inference, the Radeon PRO W7600 or the RTX PRO 4000 Blackwell?

The RTX PRO 4000 Blackwell is faster for token generation — its 672 GB/s memory bandwidth vs 288 GB/s on the Radeon PRO W7600 is the primary driver of inference throughput in autoregressive models.

Which is better for AI training?

The RTX PRO 4000 Blackwell has the advantage at 46 TFLOPS vs 21.5 TFLOPS, making training runs proportionally faster than on the Radeon PRO W7600.

Technical Specifications Comparison

Architecture & Cores

SpecificationRadeon PRO W7600RTX PRO 4000 Blackwell
ArchitectureRDNA 3Blackwell
CUDA Cores (Stream Processors / CUDA Cores)2,0488,960

Memory

SpecificationRadeon PRO W7600RTX PRO 4000 Blackwell
VRAM Capacity8 GB24 GB
Memory TypeGDDR6GDDR7
Memory Bus128-bit192-bit
Bandwidth288 GB/s672 GB/s

Connectivity & Power

SpecificationRadeon PRO W7600RTX PRO 4000 Blackwell
InterfacePCIe 4.0 x16PCIe 5.0 x16
TDP130 W140 W
ReleasedApr 2023Mar 2025

Workstation

SpecificationRadeon PRO W7600RTX PRO 4000 Blackwell
FP32 (TFLOPS)21.5 TFLOPS46 TFLOPS
ECCYesYes
NVLinkNoNo
Form factordual-slotsingle-slot