AMD Radeon AI PRO R9600D 32GB vs AMD Radeon RX 9070 GRE 12GB

Both GPUs launched in 2025: the Radeon AI PRO R9600D on RDNA 4 and the Radeon RX 9070 GRE on RDNA 4.

Dense throughput for the Radeon AI PRO R9600D against the Radeon RX 9070 GRE: FP32 25 vs 34 TFLOPS, FP16 99 vs 137 TFLOPS, FP8 199 vs 274 TFLOPS. Sparse figures, where the vendor publishes them, appear under each dense number in the performance table.

Memory is 32 GB against 12 GB, fed at 640 GB/s versus 432 GB/s. More memory per GPU means larger models fit before you have to shard across cards, which often matters more than raw TFLOPS for inference.

Power budgets are 150 W for the Radeon AI PRO R9600D and 220 W for the Radeon RX 9070 GRE. At FP32 that works out to 0.17 against 0.16 TFLOPS per watt.

For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.