MI300X vs MI355X

The MI355X demonstrates superior raw compute with 2300 TFLOPS FP16 compared to 1307 TFLOPS on MI300X, a 76% uplift ideal for AI training dominated by half-precision operations. FP32 performance leaps from 163 TFLOPS to 2300 TFLOPS, enabling 14x faster scientific simulations or graphics workloads requiring single-precision math. FP8 throughput doubles to 4600 TFLOPS from 2614 TFLOPS, accelerating quantized inference for large language models. This FP16/FP32 balance on MI355X suits mixed-precision pipelines, whereas MI300X favors FP16-heavy inference. Memory differences prove critical: 288 GB HBM3e versus 192 GB HBM3 supports 50% larger batch sizes in training, reducing overhead in transformer models exceeding 100 billion parameters. The 8000 GB/s bandwidth on MI355X versus 5300 GB/s minimizes data starvation, sustaining peak FLOPS during memory-bound tasks like diffusion models. Same 750W TDP ensures comparable power efficiency per socket.

Select the MI300X for immediate deployment in production environments. Nine live cloud offers start at $0.50 per hour with an average of $2.63 per hour, providing cost-effective access without waiting for MI355X availability. PCIe 5.0 support aids integration into existing data centers, and 192 GB HBM3 suffices for models up to 70 billion parameters in fine-tuning or inference at scale.

Choose the MI355X for future-proofing demanding AI pipelines. Its 288 GB HBM3e and 8000 GB/s bandwidth handle massive datasets in LLM training, supporting batch sizes 50% larger than MI300X limits. Balanced 2300 TFLOPS across FP16 and FP32 excels in versatile workloads like scientific computing requiring high FP32 throughput.