GPU comparison

GH200 vs Quadro RTX 4000

Specifications and current cloud pricing, side by side.

HoppervsTuringUpdated 33 days ago

The GH200 wins for the most common use case of LLM training because its 989 TFLOPS dense FP16, 96 GB VRAM, and 4000 GB/s bandwidth exceed the corresponding 57 TFLOPS dense FP16, 8 GB VRAM, and 416 GB/s bandwidth of the Quadro RTX 4000 by large margins.

GH200 listed from $1.99/GPU/hrQuadro RTX 4000 listed from $0.56/GPU/hr

Right now, from live stock

  • Cheapest right now: Quadro RTX 4000 at $0.56/hr on Paperspace

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  • Most providers in stock: Quadro RTX 4000 (1)

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Specifications Compared

SpecGH200Quadro RTX 4000
TDP900W125W
VRAM96 GB8 GB
CUDA Cores16,8962,304
FP8 (dense)1,979 TFLOPSNot published
Memory TypeHBM3GDDR6
ArchitectureHopperTuring
FP16 (dense)989 TFLOPS57 TFLOPS
Form FactorsSXMPCIe
INT8 (dense)1,979 TOPSNot published
InterconnectNVLink-C2C, PCIe 5.0PCIe 3.0
Tensor Cores528288
FP32 Performance67 TFLOPS7.1 TFLOPS
FP64 Performance34 TFLOPSNot published
Memory Bandwidth4,000 GB/s416 GB/s
FP8 (with sparsity)3,958 TFLOPSNot published
FP16 (with sparsity)1,979 TFLOPSNot published
INT8 (with sparsity)3,958 TOPSNot published

Performance Analysis

The ratio of 989 TFLOPS dense FP16 on the GH200 to 57 TFLOPS dense FP16 on the Quadro RTX 4000 indicates substantially higher throughput for matrix operations in training workloads. Inference tasks benefit similarly when both GPUs run dense FP16 at those exact figures. The 4000 GB/s bandwidth on the GH200 compared with 416 GB/s on the Quadro RTX 4000 permits larger batch sizes before memory becomes the constraint. FP32 performance stands at 67 TFLOPS on the GH200 versus 7.1 TFLOPS on the Quadro RTX 4000, affecting precision-sensitive scientific kernels. Sparsity figures remain separate with 1979 TFLOPS sparse FP16 on the GH200 and no corresponding sparse value published for the Quadro RTX 4000.

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.

Quadro RTX 4000

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
Paperspaceams11$0.56—Deploy

1 provider in stock, 5 offers (cheapest per provider shown). All Quadro RTX 4000 offers, price history and alerts

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When to Choose the GH200

The GH200 suits workloads that require 96 GB HBM3 VRAM and 989 TFLOPS dense FP16 for large model training. Its 4000 GB/s bandwidth supports sustained data movement in distributed setups with NVLink-C2C interconnect. The 900W TDP is acceptable when maximum dense FP8 performance of 1979 TFLOPS is needed.

When to Choose the Quadro RTX 4000

The Quadro RTX 4000 fits environments limited to 125W TDP and PCIe 3.0 slots where 8 GB GDDR6 VRAM suffices. Its 7.1 TFLOPS FP32 rating handles lighter inference or visualization tasks without exceeding power or form factor constraints of standard workstations.

Use Cases

LLM Training
GH200

The GH200 supplies 989 TFLOPS dense FP16 and 96 GB HBM3 VRAM while the Quadro RTX 4000 supplies only 57 TFLOPS dense FP16 and 8 GB GDDR6 VRAM.

LLM Inference
GH200

The GH200 delivers 1979 TFLOPS dense FP8 and 4000 GB/s bandwidth enabling larger concurrent batches than the Quadro RTX 4000 can sustain at 416 GB/s.

Fine-tuning
GH200

The GH200 provides 989 TFLOPS dense FP16 together with 96 GB memory for gradient accumulation on models that exceed the 8 GB limit of the Quadro RTX 4000.

Stable Diffusion
Quadro RTX 4000

The Quadro RTX 4000 meets requirements at 7.1 TFLOPS FP32 and 125W TDP for typical image generation workloads that fit within 8 GB GDDR6.

Scientific Computing
GH200

The GH200 offers 67 TFLOPS FP32 and 4000 GB/s bandwidth for memory-bound simulations that benefit from its 96 GB HBM3 capacity.

Frequently Asked Questions

What FP16 performance does the GH200 provide compared with the Quadro RTX 4000?▾

The GH200 lists 989 TFLOPS dense FP16 and 1979 TFLOPS with sparsity. The Quadro RTX 4000 lists 57 TFLOPS dense FP16 with no sparsity figure published.

Which GPU has the higher TDP rating?▾

The GH200 carries a 900W TDP rating. The Quadro RTX 4000 carries a 125W TDP rating.

What interconnect options exist on each card?▾

The GH200 supports NVLink-C2C and PCIe 5.0. The Quadro RTX 4000 supports PCIe 3.0 only.

Does the Quadro RTX 4000 publish FP8 or INT8 numbers?▾

No FP8 or INT8 figures appear for the Quadro RTX 4000. The GH200 publishes 1979 TFLOPS dense FP8 and 1979 TOPS dense INT8.

What architecture and year define each GPU?▾

The GH200 uses Hopper architecture released in 2023. The Quadro RTX 4000 uses Turing architecture released in 2018.

Which is cheaper to rent, the GH200 or the Quadro RTX 4000?▾

Cloud rental prices for both the GH200 and Quadro RTX 4000 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 Quadro RTX 4000?▾

The GH200 has 96 GB of HBM3 memory. The Quadro RTX 4000 has 8 GB of GDDR6 memory.

Can I find GH200 and Quadro RTX 4000 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 Quadro RTX 4000?▾

The GH200 uses the Hopper architecture (2023) while the Quadro RTX 4000 uses Turing (2018). The GH200 delivers 17.4x the dense FP16 throughput (989 vs 57 TFLOPS, both without sparsity) and 9.6x the memory bandwidth of the Quadro RTX 4000.

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How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the GH200 and the Quadro RTX 4000. 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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