GPU comparison

H200 vs MI300X

Specifications and current cloud pricing, side by side.

HoppervsCDNA 3Updated 44 days ago

The MI300X stands as the stronger choice for the most common use case of large model training. Its 192 GB memory and 1307.4 TFLOPS dense FP16 rating exceed the corresponding 141 GB and 989 TFLOPS values on the H200 while the higher 5300 GB/s bandwidth supports larger batch processing.

H200 from $4.44/GPU/hrMI300X from $2.59/GPU/hr

Right now, from live stock

  • Cheapest right now: MI300X at $2.59/hr on DigitalOcean

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  • Most providers in stock: H200 (3)

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  • Best $ per TFLOPS FP16 dense right now: MI300X ($0.0020 per TFLOPS-hour at 1,307.4 TFLOPS)

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Specifications Compared

SpecH200MI300X
TDP700W750W
VRAM141 GB192 GB
CUDA Cores16,896Not published
FP8 (dense)1,979 TFLOPS2,614.9 TFLOPS
Memory TypeHBM3eHBM3
ArchitectureHopperCDNA 3
FP16 (dense)989 TFLOPS1,307.4 TFLOPS
Form FactorsSXM, NVLOAM
INT8 (dense)1,979 TOPS2,614.9 TOPS
InterconnectNVLink, PCIe 5.0, InfiniBandInfinity Fabric, PCIe 5.0
Tensor Cores528Not published
FP32 Performance67 TFLOPS163.4 TFLOPS
FP64 Performance34 TFLOPS81.7 TFLOPS
Memory Bandwidth4,800 GB/s5,300 GB/s
FP8 (with sparsity)3,958 TFLOPS5,229.8 TFLOPS
FP16 (with sparsity)1,979 TFLOPS2,614.9 TFLOPS
INT8 (with sparsity)3,958 TOPS5,229.8 TOPS

Performance Analysis

The FP16 dense performance reaches 989 TFLOPS on the H200 and 1307.4 TFLOPS on the MI300X. This gap indicates the MI300X can process larger batches during training or inference steps that rely on dense FP16 operations. The FP32 rating stands at 67 TFLOPS for the H200 and 163.4 TFLOPS for the MI300X so workloads using full precision arithmetic complete more operations per second on the MI300X. Memory bandwidth of 4800 GB/s on the H200 versus 5300 GB/s on the MI300X affects the size of data batches that fit within transfer limits during model execution. Direct comparison of dense FP16 figures shows the MI300X ahead while the same holds for sparse FP16 ratings of 1979 TFLOPS on the H200 against 2614.9 TFLOPS on the MI300X.

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.

H200

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
Vast.aiCzechia, CZ1$4.44—Deploy
DigitalOceanAtlanta 11$4.47—Deploy
RunPodglobal1$5.29—Deploy

3 providers in stock, 3 offers. All H200 offers, price history and alerts

MI300X

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
DigitalOceanAtlanta 11$2.59—Deploy
Hot AisleMichigan1$2.99—Deploy

2 providers in stock, 3 offers (cheapest per provider shown). All MI300X offers, price history and alerts

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When to Choose the H200

The H200 suits environments that prioritize 700W TDP operation and NVLink interconnect availability. Its SXM and NVL form factors align with systems already configured for those interfaces while the 4800 GB/s bandwidth supports steady data movement in dense FP16 tasks rated at 989 TFLOPS.

When to Choose the MI300X

The MI300X fits scenarios that require 192 GB memory capacity and 5300 GB/s bandwidth for handling larger working sets. Its 1307.4 TFLOPS dense FP16 rating and 163.4 TFLOPS FP32 rating provide advantages in throughput for training or inference steps that scale with those metrics.

Use Cases

LLM Training
MI300X

The MI300X supplies 192 GB memory and 1307.4 TFLOPS dense FP16 which exceed the 141 GB and 989 TFLOPS on the H200.

LLM Inference
MI300X

The MI300X offers 5300 GB/s bandwidth and 2614.9 TFLOPS FP8 dense which support higher throughput than the 4800 GB/s and 1979 TFLOPS on the H200.

Fine-tuning
Either

Both GPUs deliver comparable FP16 dense ratings relative to their memory sizes of 141 GB on the H200 and 192 GB on the MI300X.

Stable Diffusion
MI300X

The MI300X provides 163.4 TFLOPS FP32 and 5300 GB/s bandwidth which aid image generation steps more than the 67 TFLOPS and 4800 GB/s on the H200.

Scientific Computing
MI300X

The MI300X achieves 163.4 TFLOPS FP32 compared to 67 TFLOPS on the H200 for precision heavy calculations.

Frequently Asked Questions

What are the dense FP16 ratings?▾

The H200 reaches 989 TFLOPS dense FP16 and the MI300X reaches 1307.4 TFLOPS dense FP16.

Which GPU has higher memory bandwidth?▾

The MI300X provides 5300 GB/s bandwidth compared to 4800 GB/s on the H200.

What TDP values apply to these GPUs?▾

The H200 lists 700W TDP and the MI300X lists 750W TDP.

Do the GPUs share the same interconnect options?▾

The H200 supports NVLink and InfiniBand while the MI300X supports Infinity Fabric.

How do the FP32 figures compare?▾

The MI300X delivers 163.4 TFLOPS FP32 against 67 TFLOPS FP32 on the H200.

Which is cheaper to rent, the H200 or the MI300X?▾

Cloud rental prices for both the H200 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 H200 have compared to the MI300X?▾

The H200 has 141 GB of HBM3e memory. The MI300X has 192 GB of HBM3 memory.

Can I find H200 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 H200 and the MI300X?▾

The H200 uses the Hopper architecture (2024) while the MI300X uses CDNA 3 (2023). The MI300X delivers 1.3x the dense FP16 throughput (1,307.4 vs 989 TFLOPS, both without sparsity) and 1.1x the memory bandwidth of the H200.

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Related comparisons

How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the H200 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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