> The iGPU on Strix Point can do 9tflops of good old fp32. Unsure what the TFlOps drops to on the new Jetson here as it goes from INT8->FP32. But probably still

> The iGPU on Strix Point can do 9tflops of good old fp32. Unsure what the TFlOps drops to on the new Jetson here as it goes from INT8->FP32. But probably still has a very healthy lead. Not as much as you think. Per their developer blog [1], it only has 17.1 FP16 Tensor TFLOPS, so about neck and neck w/ the even the last gen (7840/8840) Radeon 780Ms. The Orin Nano Super looks like a neat little board at a great price ($250) and wattage (25W), but basically if you are doing FP16 inference, it's more incremental than revolutionary - vs AMD it's a bit cheaper (7840 miniPCs are as low as $400 atm, there's an upcoming SBC that's launching at $330), a bit more efficient (you'll probably need 30-45W to get the max perf on the AMD board), and with better INT8 (note the 67 TOPS is sparse, it's only 33 TOPS of dense INT8), but w/ the AMD boards you can get a lot more memory (you'll need to use UMA to access it). Strix Point's NPU can match on INT8 perf, but those minipcs are selling for like $1000 and I haven't seen any SBCs so not very good price/perf there yet. As another point of reference btw, since the Orin Nano Super is using (32) Ampere Tensor cores @ 1020 MHz. A $170 RTX 3050 has 72 Ampere Tensor Cores @ 1470 MHz w/ 168 GB/s of MBW (6GB VRAM) @ 70W. You'll expect 1/3 the compute and half the inference perf. Again, not bad for the power envelope, and a better form factor, but you aren't really getting much for "free" so to speak. As a performance target (more MBW, more FLOPS), I'm more excited for Strix Halo and Orin Thor as a better fit for inferencing bigger models, but it seems like both AMD and Nvidia are going to continue charging an arm and a leg for those new products. [1] https://developer.nvidia.com/blog/nvidia-jetson-orin-nano-developer-kit-gets-a-super-boost/ https://developer.nvidia.com/blog/nvidia-jetson-orin-nano-de...