GPU comparison

GH200 vs RTX 6000 Ada

Specifications and current cloud pricing, side by side.

HoppervsAda LovelaceUpdated 23 days ago

The GH200 wins for the most common use case of LLM training because its 96 GB memory, 4000 GB/s bandwidth, and 989 TFLOPS dense FP16 exceed the corresponding figures on the RTX 6000 Ada Generation.

GH200 listed from $1.99/GPU/hrRTX 6000 Ada listed from $0.78/GPU/hr

Right now, from live stock

  • Cheapest right now: RTX 6000 Ada at $0.78/hr on QuantaCloud

    Deploy
  • Most providers in stock: RTX 6000 Ada (4)

    See all offers

Specifications Compared

SpecGH200RTX 6000 Ada
TDP900W300W
VRAM96 GB48 GB
CUDA Cores16,89618,176
FP8 (dense)1,979 TFLOPS728.5 TFLOPS
Memory TypeHBM3GDDR6
ArchitectureHopperAda Lovelace
FP16 (dense)989 TFLOPS364 TFLOPS
Form FactorsSXMPCIe
INT8 (dense)1,979 TOPS728.5 TOPS
InterconnectNVLink-C2C, PCIe 5.0PCIe 4.0
Tensor Cores528568
FP32 Performance67 TFLOPS91.1 TFLOPS
FP64 Performance34 TFLOPSNot published
Memory Bandwidth4,000 GB/s960 GB/s
FP8 (with sparsity)3,958 TFLOPS1,457 TFLOPS
FP16 (with sparsity)1,979 TFLOPS728 TFLOPS
INT8 (with sparsity)3,958 TOPS1,457 TOPS

Performance Analysis

Dense FP16 performance reaches 989 TFLOPS on the GH200 compared with 364 TFLOPS on the RTX 6000 Ada Generation. This gap translates to faster model training and inference cycles when applications rely on dense half precision arithmetic. Memory bandwidth of 4000 GB/s versus 960 GB/s permits the GH200 to accommodate larger batch sizes without frequent data movement. With sparsity the GH200 attains 1979 TFLOPS FP16 while the RTX 6000 Ada Generation reaches 728 TFLOPS FP16. FP32 throughput stands at 67 TFLOPS for the GH200 and 91.1 TFLOPS for the RTX 6000 Ada Generation.

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 6000 Ada

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
QuantaCloudus-midwest-24$0.78$3.11Deploy
Massed Computeus-central-32$0.79$1.58Deploy
LeaderGPUThe Netherlands8$1.20$9.60Deploy
VERDAFIN-HEL1$1.21—Deploy

4 providers in stock, 14 offers (cheapest per provider shown). All RTX 6000 Ada offers, price history and alerts

Which GPU to watchWatch the price of

Notify me when GH200 drops below a price

One email when the cheapest in-stock on-demand price per GPU-hour falls below your threshold.

QuantaCloud

Comparing H-series providers? We broker across all of them.

Hopper stock changes by the hour and prices differ by provider. If you need 16+ GPUs reserved or a cluster in the next 90 days, we quote H-series or B300 inventory at partner rates: one quote, 24h turnaround.

No waitlist24hr quote turnaroundInfiniBand fabric

Compare real-time pricing across 25+ providers

When to Choose the GH200

The GH200 suits LLM training tasks that require 96 GB HBM3 capacity and 4000 GB/s bandwidth to hold extensive model states. Its 989 TFLOPS dense FP16 rating supports accelerated half precision workloads that exceed the 364 TFLOPS dense FP16 of the alternative.

When to Choose the RTX 6000 Ada

The RTX 6000 Ada Generation fits scientific computing jobs that depend on 91.1 TFLOPS FP32 throughput and a 300W TDP limit. Its PCIe form factor also aligns with systems that operate under the 900W TDP of the GH200.

Use Cases

LLM Training
GH200

The GH200 supplies 96 GB HBM3 memory and 989 TFLOPS dense FP16 to handle large models in half precision.

LLM Inference
GH200

Its 4000 GB/s bandwidth and 1979 TFLOPS FP16 with sparsity enable higher throughput for inference batches.

Fine-tuning
GH200

The 989 TFLOPS dense FP16 and 96 GB capacity support efficient adaptation of models that exceed 48 GB limits.

Stable Diffusion
RTX 6000 Ada

The RTX 6000 Ada Generation delivers 91.1 TFLOPS FP32 within a 300W TDP for image generation workloads.

Scientific Computing
RTX 6000 Ada

Its 91.1 TFLOPS FP32 rating provides an advantage over the 67 TFLOPS FP32 of the GH200.

Frequently Asked Questions

What are the dense FP16 ratings for each GPU?▾

The GH200 reaches 989 TFLOPS dense FP16 and the RTX 6000 Ada Generation reaches 364 TFLOPS dense FP16.

Which GPU offers higher FP32 performance?▾

The RTX 6000 Ada Generation provides 91.1 TFLOPS FP32 compared with 67 TFLOPS FP32 on the GH200.

How does memory bandwidth compare?▾

The GH200 achieves 4000 GB/s bandwidth while the RTX 6000 Ada Generation achieves 960 GB/s bandwidth.

What TDP values apply to these GPUs?▾

The GH200 lists a 900W TDP and the RTX 6000 Ada Generation lists a 300W TDP.

Which is cheaper to rent, the GH200 or the RTX 6000 Ada?▾

Cloud rental prices for both the GH200 and RTX 6000 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 6000 Ada?▾

The GH200 has 96 GB of HBM3 memory. The RTX 6000 Ada has 48 GB of GDDR6 memory.

Can I find GH200 and RTX 6000 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 6000 Ada?▾

The GH200 uses the Hopper architecture (2023) while the RTX 6000 Ada uses Ada Lovelace (2022). The GH200 delivers 2.7x the dense FP16 throughput (989 vs 364 TFLOPS, both without sparsity) and 4.2x the memory bandwidth of the RTX 6000 Ada.

Rent these GPUs

Each GPU page lists every current on-demand offer by provider, per GPU-hour, updated every minute.

Related comparisons

How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the GH200 and the RTX 6000 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.

Next steps