Specifications Compared
| Spec | GH200 | RTX-4060 |
|---|---|---|
| TDP | 900W | 115W |
| VRAM | 96 GB | 8 GB |
| CUDA Cores | 16,896 | 3,072 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Ada Lovelace |
| Form Factors | SXM | PCIe |
| Interconnect | NVLink-C2C, PCIe 5.0 | |
| Tensor Cores | 528 | 96 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 15.1 TFLOPS |
| FP32 Performance | 67 TFLOPS | 15.1 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 242 TOPS |
| Memory Bandwidth | 4,000 GB/s | 272 GB/s |
Performance Analysis
Compute specifications reveal profound gaps suited to different workloads. The GH200's 1979 TFLOPS FP16 performance vastly exceeds the RTX 4060 Ti's 15.1 TFLOPS, enabling faster AI model training where half-precision operations dominate. Its FP32 rate of 67 TFLOPS surpasses the RTX 4060 Ti's 15.1 TFLOPS, benefiting general-purpose computing tasks. FP8 capability at 3958 TFLOPS on GH200 accelerates inference for quantized large language models, unavailable at scale on RTX 4060 Ti. These deltas translate to GH200 handling training epochs in minutes rather than hours for models exceeding 8 GB VRAM. Memory differences amplify this: GH200's 96 GB HBM3 and 4000 GB/s bandwidth support massive batch sizes without swapping, while RTX 4060 Ti's 8 GB GDDR6 and 272 GB/s limit it to small batches prone to out-of-memory errors. Power draw underscores efficiency contexts: GH200's 900W TDP suits rack-scale systems, RTX 4060 Ti's 115W fits edge or desktop use.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
GH200 Grace Hopper
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
 Denvr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 7600GB Storage | Virginia | $3.87/GPU/hr | |||
 CoreWeave | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 7680GB Storage | United States | $6.50/GPU/hr |
When to Choose the GH200 Grace Hopper
Opt for the GH200 in large-scale AI training or inference where high VRAM and bandwidth prove essential. Its 96 GB HBM3 handles models like 70B-parameter LLMs without partitioning, and 4000 GB/s bandwidth sustains throughput for batch sizes over 100. Cloud deployments at $1.99 per hour justify it for enterprises processing petabytes daily.
When to Choose the RTX 4060 Ti
Select the RTX 4060 Ti for cost-sensitive gaming, prototyping, or lightweight inference at $0.08 per hour. Its 115W TDP and PCIe form factor enable easy desktop integration, while 15.1 TFLOPS FP16 suffices for Stable Diffusion at 512x512 resolutions or fine-tuning small models under 8 GB VRAM.
Use Cases
GH200's 1979 TFLOPS FP16 and 96 GB HBM3 enable training of large models with large batch sizes. RTX 4060 Ti's 15.1 TFLOPS and 8 GB VRAM cannot handle such scales.
GH200's 3958 TFLOPS FP8 and 4000 GB/s bandwidth support high-throughput quantized inference. RTX 4060 Ti lacks FP8 scale and sufficient memory for production loads.
GH200's 67 TFLOPS FP32 and vast VRAM accelerate fine-tuning of billion-parameter models. RTX 4060 Ti suits only small adapters due to 8 GB constraint.
RTX 4060 Ti's 15.1 TFLOPS FP16 generates images at 15-30 iterations per second affordably. GH200 overkill for consumer creative tasks at $3.59 per hour.
GH200's 67 TFLOPS FP32 and NVLink-C2C interconnect excel in simulations requiring high precision. RTX 4060 Ti's lower specs limit complex datasets.
Frequently Asked Questions
Which GPU has more VRAM: GH200 or RTX 4060 Ti?▾
The GH200 provides 96 GB HBM3 VRAM, far exceeding the RTX 4060 Ti's 8 GB GDDR6. This enables GH200 to load massive datasets without issues. RTX 4060 Ti suits smaller workloads.
How do FP16 performances compare between GH200 and RTX 4060 Ti?▾
GH200 achieves 1979 TFLOPS in FP16, compared to RTX 4060 Ti's 15.1 TFLOPS. This gap favors GH200 for AI training speedups of over 100x. RTX 4060 Ti handles basic tensor operations.
What is the memory bandwidth difference?▾
GH200 offers 4000 GB/s bandwidth with HBM3, versus RTX 4060 Ti's 272 GB/s GDDR6. Higher bandwidth on GH200 supports larger batches in deep learning. RTX 4060 Ti bottlenecks at high resolutions.
Which is cheaper in the cloud?▾
RTX 4060 Ti starts at $0.08 per hour averaging $0.14 per hour across six offers. GH200 begins at $1.99 per hour averaging $3.59 per hour over four offers. Budget tasks favor RTX 4060 Ti.
What are the TDPs of these GPUs?▾
GH200 consumes 900W TDP in SXM form factor for data centers. RTX 4060 Ti uses 115W TDP in PCIe slots for desktops. Lower TDP makes RTX 4060 Ti more power-efficient for light use.
Does GH200 support FP8?▾
GH200 delivers 3958 TFLOPS in FP8 for efficient inference. RTX 4060 Ti lacks comparable FP8 specs. This positions GH200 for quantized LLM serving.
Which is cheaper to rent, the GH200 or the RTX 4060?▾
Cloud rental prices for both the GH200 and RTX 4060 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 4060?▾
The GH200 has 96 GB of HBM3 memory. The RTX 4060 has 8 GB of GDDR6 memory.
Can I find GH200 and RTX 4060 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 4060?▾
The GH200 uses the Hopper architecture (2023) while the RTX 4060 uses Ada Lovelace (2023). The GH200 delivers 131.1x the FP16 throughput and 14.7x the memory bandwidth of the RTX 4060.