GPU Comparison
Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.
Its memory bandwidth is 29% higher (360 GB/s vs 280 GB/s), translating directly to faster inference throughput.
Maximum Capacity Reached. Remove a model to add another. (2/2)
RTX 4000 Ada Generation vs RTX 4000 SFF Ada Generation: 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 4000 Ada Generation delivers 360 GB/s versus 280 GB/s on the RTX 4000 SFF Ada Generation, a 29% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX 4000 Ada Generation 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 4000 Ada Generation delivers 26.7 TFLOPS against 19.2 TFLOPS for the RTX 4000 SFF Ada Generation — a 39% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX 4000 Ada Generation.
Which should you buy: RTX 4000 Ada Generation or RTX 4000 SFF Ada Generation?
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.