GPU comparison

GH200 vs RTX 2060

Specifications and current cloud pricing, side by side.

HoppervsTuringUpdated 33 days ago

The GH200 is the stronger choice for the most common use case of LLM inference because its 96 GB memory capacity and 4000 GB/s bandwidth exceed the RTX 2060 specifications by wide margins while its 67 TFLOPS FP32 rating supports higher throughput.

GH200 listed from $1.99/GPU/hr

Specifications Compared

SpecGH200RTX 2060
TDP900W160W
VRAM96 GB6-12 GB
CUDA Cores16,8961,920
FP8 (dense)1,979 TFLOPSNot published
Memory TypeHBM3GDDR6
ArchitectureHopperTuring
FP16 (dense)989 TFLOPSNot published
Form FactorsSXMPCIe
INT8 (dense)1,979 TOPSNot published
InterconnectNVLink-C2C, PCIe 5.0PCIe 3.0
Tensor Cores528240
FP32 Performance67 TFLOPS6.5 TFLOPS
FP64 Performance34 TFLOPSNot published
Memory Bandwidth4,000 GB/s336 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 GH200 FP32 performance at 67 TFLOPS exceeds the RTX 2060 FP32 performance at 6.5 TFLOPS by a factor of ten. Memory bandwidth of 4000 GB/s on the GH200 versus 336 GB/s on the RTX 2060 permits substantially larger batch sizes during computation. The GH200 also lists dense FP16 performance at 989 TFLOPS and FP16 performance with sparsity at 1979 TFLOPS while the RTX 2060 publishes no FP16 figures.

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 2060

RTX 2060 is not offered on-demand by any provider we track right now. See the RTX 2060 rental page for last-seen listed prices and a price alert.

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 workloads that require 96 GB of memory and 4000 GB/s bandwidth together with 67 TFLOPS of FP32 performance. Its 900W TDP and SXM form factor support sustained operation on large scale scientific computing tasks.

When to Choose the RTX 2060

The RTX 2060 fits scenarios limited to 160W TDP and PCIe form factor where 6.5 TFLOPS of FP32 performance meets the requirement. Its 6 to 12 GB memory capacity aligns with smaller consumer graphics workloads.

Use Cases

LLM Training
GH200

The GH200 supplies 96 GB memory and 4000 GB/s bandwidth that exceed the RTX 2060 limits.

LLM Inference
GH200

The GH200 67 TFLOPS FP32 rating and 989 TFLOPS dense FP16 rating enable larger models than the RTX 2060 6.5 TFLOPS FP32 rating.

Fine-tuning
GH200

The GH200 1979 TFLOPS FP16 performance with sparsity supports efficient updates on 96 GB memory.

Stable Diffusion
RTX 2060

The RTX 2060 160W TDP and 6.5 TFLOPS FP32 rating suffice for typical image generation workloads.

Scientific Computing
GH200

The GH200 67 TFLOPS FP32 performance and 4000 GB/s bandwidth handle large datasets beyond RTX 2060 capacity.

Frequently Asked Questions

What is the FP32 performance difference between the GH200 and the RTX 2060?▾

The GH200 reaches 67 TFLOPS in FP32 while the RTX 2060 reaches 6.5 TFLOPS in FP32.

Which GPU has higher memory bandwidth?▾

The GH200 provides 4000 GB/s memory bandwidth compared to 336 GB/s on the RTX 2060.

What TDP ratings apply to the GH200 and the RTX 2060?▾

The GH200 lists a 900W TDP and the RTX 2060 lists a 160W TDP.

Can the RTX 2060 run dense FP16 workloads at the same level as the GH200?▾

The RTX 2060 does not publish FP16 figures while the GH200 lists 989 TFLOPS dense FP16 performance.

Which is cheaper to rent, the GH200 or the RTX 2060?▾

Cloud rental prices for both the GH200 and RTX 2060 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 2060?▾

The GH200 has 96 GB of HBM3 memory. The RTX 2060 has 6 to 12 GB of GDDR6 memory.

Can I find GH200 and RTX 2060 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 2060?▾

The GH200 uses the Hopper architecture (2023) while the RTX 2060 uses Turing (2019). The GH200 has 96 GB of HBM3 at 4,000 GB/s; the RTX 2060 has 6-12 GB of GDDR6 at 336 GB/s, so the GH200 has 11.9x the memory bandwidth of the RTX 2060.

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 2060. 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