GPU comparison

GH200 vs RTX 5000 Ada

Specifications and current cloud pricing, side by side.

HoppervsAda LovelaceUpdated 34 days ago

The GH200 wins for the most common use case of LLM training and inference. Its 96 GB HBM3 memory, 4000 GB/s bandwidth, and 989 TFLOPS FP16 dense rating deliver the capacity and speed required for contemporary large models that the RTX 5000 Ada Generation cannot accommodate.

GH200 listed from $1.99/GPU/hrRTX 5000 Ada listed from $0.55/GPU/hr

Specifications Compared

SpecGH200RTX 5000 Ada
TDP900W250W
VRAM96 GB32 GB
CUDA Cores16,89612,800
FP8 (dense)1,979 TFLOPSNot published
Memory TypeHBM3GDDR6
ArchitectureHopperAda Lovelace
FP16 (dense)989 TFLOPSNot published
Form FactorsSXMPCIe
INT8 (dense)1,979 TOPSNot published
InterconnectNVLink-C2C, PCIe 5.0PCIe 4.0
Tensor Cores528400
FP32 Performance67 TFLOPS65.3 TFLOPS
FP64 Performance34 TFLOPSNot published
Memory Bandwidth4,000 GB/s576 GB/s
FP8 (with sparsity)3,958 TFLOPS1,044.4 TFLOPS
FP16 (with sparsity)1,979 TFLOPSNot published
INT8 (with sparsity)3,958 TOPSNot published

Performance Analysis

The GH200 lists FP16 dense performance at 989 TFLOPS while the RTX 5000 Ada Generation does not publish an FP16 figure. The GH200 FP32 rating of 67 TFLOPS sits close to the RTX 5000 Ada Generation rating of 65.3 TFLOPS yet the 4000 GB/s memory bandwidth versus 576 GB/s allows substantially larger batch sizes during both training and inference passes. The GH200 also lists FP8 dense performance at 1979 TFLOPS and FP8 with sparsity at 3958 TFLOPS. The RTX 5000 Ada Generation lists FP8 with sparsity at 1044.4 TFLOPS. The sixfold bandwidth advantage on the GH200 directly expands feasible batch sizes for large models while the similar FP32 numbers indicate comparable throughput on traditional scientific kernels. The 900W TDP versus 250W TDP further separates sustained performance envelopes in dense versus sparse tensor operations.

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.

GH200

GH200 is not offered on-demand by any provider we track right now. See the GH200 rental page for last-seen listed prices and a price alert.

RTX 5000 Ada

RTX 5000 Ada is not offered on-demand by any provider we track right now. See the RTX 5000 Ada rental page for last-seen listed prices and a price alert.

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When to Choose the GH200

The GH200 suits LLM training runs that require the full 96 GB HBM3 capacity and 4000 GB/s bandwidth to maintain large batch sizes. Its 989 TFLOPS FP16 dense rating and 1979 TFLOPS FP8 dense rating accelerate both training and inference of models that exceed 32 GB footprints.

When to Choose the RTX 5000 Ada

The RTX 5000 Ada Generation fits deployments where the 250W TDP and PCIe form factor reduce infrastructure demands. Its 65.3 TFLOPS FP32 rating remains adequate for smaller fine-tuning jobs or Stable Diffusion workloads that stay within the 32 GB GDDR6 limit.

Use Cases

LLM Training
GH200

The 96 GB HBM3 capacity and 4000 GB/s bandwidth support the batch sizes needed for full scale training runs.

LLM Inference
GH200

The 989 TFLOPS FP16 dense rating combined with 96 GB memory enables low latency serving of large models.

Fine-tuning
GH200

The 1979 TFLOPS FP8 dense rating accelerates adapter updates on models that exceed 32 GB.

Stable Diffusion
RTX 5000 Ada

The 250W TDP and 65.3 TFLOPS FP32 rating suffice for diffusion workloads that fit in 32 GB GDDR6.

Scientific Computing
Either

The FP32 ratings of 67 TFLOPS and 65.3 TFLOPS are nearly identical for kernels that do not require high bandwidth.

Frequently Asked Questions

What is the memory difference between GH200 and RTX 5000 Ada?▾

The GH200 supplies 96 GB HBM3 memory while the RTX 5000 Ada Generation supplies 32 GB GDDR6 memory. The bandwidth figures are 4000 GB/s versus 576 GB/s.

How do the FP32 ratings compare?▾

The GH200 lists 67 TFLOPS FP32 and the RTX 5000 Ada Generation lists 65.3 TFLOPS FP32. These values are the only FP32 numbers published for each device.

Which GPU offers higher FP8 performance?▾

The GH200 lists 1979 TFLOPS FP8 dense and 3958 TFLOPS FP8 with sparsity. The RTX 5000 Ada Generation lists 1044.4 TFLOPS FP8 with sparsity.

What power levels do the GPUs require?▾

The GH200 carries a 900W TDP while the RTX 5000 Ada Generation carries a 250W TDP. These values determine cooling and power delivery requirements.

Can the RTX 5000 Ada Generation run models larger than 32 GB?▾

No. The device provides 32 GB GDDR6 memory so any workload exceeding that capacity must use the GH200 with its 96 GB HBM3 memory.

Which is cheaper to rent, the GH200 or the RTX 5000 Ada?▾

Cloud rental prices for both the GH200 and RTX 5000 Ada 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 GH200 have compared to the RTX 5000 Ada?▾

The GH200 has 96 GB of HBM3 memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.

Can I find GH200 and RTX 5000 Ada 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 GH200 and the RTX 5000 Ada?▾

The GH200 uses the Hopper architecture (2023) while the RTX 5000 Ada uses Ada Lovelace (2023). The GH200 has 96 GB of HBM3 at 4,000 GB/s; the RTX 5000 Ada has 32 GB of GDDR6 at 576 GB/s, so the GH200 has 6.9x the memory bandwidth of the RTX 5000 Ada.

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How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the GH200 and the RTX 5000 Ada. 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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