GPU Comparison
Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.
Its memory bandwidth is 75% higher (672 GB/s vs 384 GB/s), translating directly to faster inference throughput.
Maximum Capacity Reached. Remove a model to add another. (2/2)
Arc Pro A60 vs RTX PRO 4000 Blackwell: In-Depth Breakdown
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 384 GB/s on the Arc Pro A60, a 75% 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 14.7 TFLOPS for the Arc Pro A60 — a 213% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX PRO 4000 Blackwell.
Which should you buy: Arc Pro A60 or RTX PRO 4000 Blackwell?
Both cards serve similar workloads. Base your decision on whichever spec matters most: VRAM for model capacity, memory bandwidth for inference speed, and FP32 compute for training throughput.