MI300X vs RTX 4070 Ti

The MI300X family delivers FP16 dense throughput of 1307.4 TFLOPS compared with the RTX 4070 family delivery of 58.3 TFLOPS dense. This gap means the MI300X family completes dense FP16 matrix operations more than twenty times faster than the RTX 4070 family during training workloads. The same families report FP16 with sparsity figures of 2614.9 TFLOPS and 116.6 TFLOPS respectively so sparsity ratios remain comparable across both platforms. Memory bandwidth of 5300 GB/s on the MI300X family versus 504 GB/s on the RTX 4070 family permits substantially larger batch sizes before memory capacity limits are reached. FP32 throughput sits at 163.4 TFLOPS for the MI300X family and 29.1 TFLOPS for the RTX 4070 family.

The MI300X variant with 192 GB HBM3 memory suits workloads that require the full 192 GB capacity to hold large model states during training or inference. Its 5300 GB/s bandwidth and 750 W TDP support sustained high throughput on dense FP16 operations rated at 1307.4 TFLOPS.

The RTX 4070 Ti variant with 12 GB GDDR6X memory fits compact inference or fine tuning jobs where the 200 W TDP and PCIe form factor reduce power and cooling demands. Its FP16 dense rating of 58.3 TFLOPS remains adequate for models that fit inside the 12 GB limit.