GPU comparison

GB300 SXM6 vs MI300X

Specifications and current cloud pricing, side by side.

Blackwell UltravsCDNA 3Updated 33 days ago

This variant comparison is part of the GB300 vs MI300X family comparison.

The GB300 SXM6 wins for the most common large language model workloads because its 2250 TFLOPS dense FP16 rating and 288 GB memory capacity exceed the corresponding 1307.4 TFLOPS dense FP16 rating and 192 GB capacity of the MI300X.

GB300 SXM6 listed from $7.99/GPU/hrMI300X listed from $0.95/GPU/hr

Specifications Compared

SpecGB300 SXM6MI300X
TDP1400W750W
VRAM288 GB192 GB
FP4 (dense)13,500 TFLOPSNot published
FP8 (dense)4,500 TFLOPS2,614.9 TFLOPS
Memory TypeHBM3eHBM3
ArchitectureBlackwell UltraCDNA 3
FP16 (dense)2,250 TFLOPS1,307.4 TFLOPS
Form FactorsSXM6OAM
INT8 (dense)187.5 TOPS2,614.9 TOPS
InterconnectNVLink, PCIe 6.0, InfiniBandInfinity Fabric, PCIe 5.0
FP32 Performance75 TFLOPS163.4 TFLOPS
FP64 Performance1.25 TFLOPS81.7 TFLOPS
Memory Bandwidth8,000 GB/s5,300 GB/s
FP4 (with sparsity)18,000 TFLOPSNot published
FP8 (with sparsity)9,000 TFLOPS5,229.8 TFLOPS
FP16 (with sparsity)4,500 TFLOPS2,614.9 TFLOPS
INT8 (with sparsity)375 TOPS5,229.8 TOPS

Performance Analysis

The GB300 SXM6 achieves 2250 TFLOPS in dense FP16 compared to the MI300X at 1307.4 TFLOPS in dense FP16 which translates to greater throughput for matrix operations during large model training runs. The MI300X reaches 163.4 TFLOPS in FP32 while the GB300 SXM6 reaches 75 TFLOPS in FP32 so the MI300X supplies higher performance for precision sensitive scientific simulations. Memory bandwidth of 8000 GB/s on the GB300 SXM6 versus 5300 GB/s on the MI300X allows larger batch sizes in dense FP16 inference tasks before memory capacity limits of 288 GB versus 192 GB become the constraint.

Current On-Demand Offers

Cheapest secure on-demand offer per provider that is reported in stock right now, per GPU per hour; multi-GPU instances show the whole-instance price alongside. Deploy opens the DeployGPU console for providers on the platform, otherwise the provider's own site. Stock is rechecked every minute.

GB300 SXM6

GB300 SXM6 is not offered on-demand by any provider we track right now. See the GB300 SXM6 rental page for last-seen listed prices and a price alert.

MI300X

MI300X is not offered on-demand by any provider we track right now. See the MI300X rental page for last-seen listed prices and a price alert.

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When to Choose the GB300 SXM6

The GB300 SXM6 suits deployments that require 288 GB HBM3e capacity and 8000 GB/s bandwidth for training models that exceed 192 GB footprints. Its 2250 TFLOPS dense FP16 rating supports higher throughput in transformer based workloads compared to the 1307.4 TFLOPS dense FP16 rating of the alternative.

When to Choose the MI300X

The MI300X fits environments that prioritize 750 W TDP and 163.4 TFLOPS FP32 performance for compute bound scientific applications. Its OAM form factor and Infinity Fabric interconnect match systems already configured for CDNA 3 hardware with 192 GB HBM3 capacity.

Use Cases

LLM Training
GB300 SXM6

The GB300 SXM6 supplies 2250 TFLOPS dense FP16 and 288 GB memory which exceed the 1307.4 TFLOPS dense FP16 and 192 GB memory of the MI300X.

LLM Inference
GB300 SXM6

The GB300 SXM6 delivers 2250 TFLOPS dense FP16 along with 8000 GB/s bandwidth that supports larger batch sizes than the 1307.4 TFLOPS dense FP16 and 5300 GB/s bandwidth of the MI300X.

Fine-tuning
GB300 SXM6

The GB300 SXM6 provides 288 GB HBM3e capacity that accommodates fine tuning runs beyond the 192 GB limit of the MI300X.

Stable Diffusion
Either

Both GPUs handle the workload with the GB300 SXM6 offering higher dense FP16 throughput while the MI300X provides lower 750 W TDP.

Scientific Computing
MI300X

The MI300X achieves 163.4 TFLOPS FP32 which surpasses the 75 TFLOPS FP32 of the GB300 SXM6.

Frequently Asked Questions

How does dense FP16 performance compare between these GPUs?▾

The GB300 SXM6 reaches 2250 TFLOPS in dense FP16 while the MI300X reaches 1307.4 TFLOPS in dense FP16.

What TDP ratings apply to the GB300 SXM6 and MI300X?▾

The GB300 SXM6 operates at 1400 W TDP while the MI300X operates at 750 W TDP.

Which GPU offers higher FP32 throughput?▾

The MI300X delivers 163.4 TFLOPS in FP32 compared to 75 TFLOPS in FP32 on the GB300 SXM6.

How does memory bandwidth differ between the two?▾

The GB300 SXM6 provides 8000 GB/s memory bandwidth while the MI300X provides 5300 GB/s memory bandwidth.

Which is cheaper to rent, the GB300 SXM6 or the MI300X?▾

Cloud rental prices for both the GB300 SXM6 and MI300X vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.

How much VRAM does the GB300 SXM6 have compared to the MI300X?▾

The GB300 SXM6 has 288 GB of HBM3e memory. The MI300X has 192 GB of HBM3 memory.

Can I find GB300 SXM6 and MI300X GPUs available to rent right now?▾

Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.

What is the main difference between the GB300 SXM6 and the MI300X?▾

The GB300 SXM6 uses the Blackwell Ultra architecture (2025) while the MI300X uses CDNA 3 (2023). The GB300 SXM6 delivers 1.7x the dense FP16 throughput (2,250 vs 1,307.4 TFLOPS, both without sparsity) and 1.5x the memory bandwidth of the MI300X.

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Related comparisons

How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the GB300 SXM6 and the MI300X. Dense and sparse throughput are listed separately.
  • Prices and availability are live: every offer shown is an in-stock, on-demand listing from a provider we track, rechecked every minute.
  • The written comparison (overview, performance notes, when to choose each card, verdict, use cases and FAQ) was drafted with an AI model from the specification table above and passed an automated check that rejects any figure not in that table. It was last generated on . It contains no prices; those are always read live.
  • Read how we collect the data, or report an error on this page.

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