Specifications Compared
| Spec | GH200 | RTX-4070 |
|---|---|---|
| TDP | 900W | 200W |
| VRAM | 96 GB | 12 GB |
| CUDA Cores | 16,896 | 5,888 |
| Memory Type | HBM3 | GDDR6X |
| Architecture | Hopper | Ada Lovelace |
| Form Factors | SXM | PCIe |
| Interconnect | NVLink-C2C, PCIe 5.0 | |
| Tensor Cores | 528 | 184 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 29.1 TFLOPS |
| FP32 Performance | 67 TFLOPS | 29.1 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | 466 TOPS |
| Memory Bandwidth | 4,000 GB/s | 504 GB/s |
Performance Analysis
The GH200's FP16 performance reaches 1979 TFLOPS compared to the RTX 4070's 29.1 TFLOPS: this gap accelerates deep learning training where half-precision computations dominate. For inference, the GH200's FP8 capability at 3958 TFLOPS further widens the lead, enabling deployment of models with billions of parameters at scale. The RTX 4070's equal FP16 and FP32 at 29.1 TFLOPS suits mixed-precision gaming or smaller neural networks but falters on large-scale AI.
Memory specs define batch size limits: the GH200's 96 GB HBM3 and 4000 GB/s bandwidth support enormous batches in transformer models, reducing training time significantly. The RTX 4070's 12 GB GDDR6X and 504 GB/s constrain it to modest datasets, risking out-of-memory errors on complex tasks. Power draw underscores efficiency differences, with the GH200 at 900W for SXM form factor versus the RTX 4070's 200W PCIe design, impacting datacenter versus desktop deployments.
Interconnects highlight scalability: GH200 employs NVLink-C2C and PCIe 5.0 for multi-GPU clusters, while the RTX 4070 lacks advanced linking, limiting it to single-card setups.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
GH200
| 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 |
RTX 4070
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA GeForce RTX 4070 Ti 12GB VRAM | 12GB | 6 vCPU 30GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the GH200
Enterprises tackling large language model training select the GH200: its 96 GB VRAM and 1979 TFLOPS FP16 handle datasets exceeding 12 GB capacities of consumer GPUs. Data centers benefit from 4000 GB/s bandwidth for high-throughput inference at 3958 TFLOPS FP8, paired with NVLink-C2C for seamless scaling across nodes.
Scientific simulations or HPC workloads demand the GH200's 67 TFLOPS FP32 and 900W TDP tolerance in SXM form factors, unavailable on PCIe-limited alternatives.
When to Choose the RTX 4070
Budget-conscious developers or gamers prefer the RTX 4070: at $0.07 per hour average $0.19, it delivers 29.1 TFLOPS FP32 for real-time rendering and light fine-tuning without enterprise costs. Its 200W TDP fits desktops or small clusters, avoiding the GH200's 900W power infrastructure.
Prototyping small models or Stable Diffusion tasks thrives on 12 GB VRAM and 504 GB/s bandwidth, where the RTX 4070's PCIe form factor enables easy local deployment.
Use Cases
GH200's 1979 TFLOPS FP16 and 96 GB HBM3 VRAM support massive batch sizes for training models with billions of parameters. RTX 4070's 12 GB limits it to toy datasets.
GH200's 3958 TFLOPS FP8 and 4000 GB/s bandwidth enable high-throughput serving of large models. RTX 4070 handles only smaller inferences efficiently.
GH200's 67 TFLOPS FP32 and NVLink-C2C scaling accelerate parameter-efficient fine-tuning on huge datasets. RTX 4070 suffices for small models but scales poorly.
RTX 4070's 29.1 TFLOPS FP16 and 504 GB/s bandwidth generate images quickly at low $0.07 per hour cost. GH200 overkill for single-user creative tasks.
GH200's 96 GB VRAM and PCIe 5.0 handle complex simulations with large matrices. RTX 4070's 12 GB VRAM restricts precision-demanding computations.
Frequently Asked Questions
Which GPU has more VRAM, GH200 or RTX 4070?▾
The GH200 provides 96 GB HBM3 VRAM, eight times the RTX 4070's 12 GB GDDR6X. This enables GH200 to load much larger models without swapping. RTX 4070 suits memory-light applications.
How do cloud prices compare for GH200 and RTX 4070?▾
GH200 starts at $1.99 per hour with $3.59 average across four offers. RTX 4070 begins at $0.07 per hour averaging $0.19 over nine providers. RTX 4070 offers better value for entry-level use.
What is the FP16 performance difference?▾
GH200 delivers 1979 TFLOPS FP16 versus RTX 4070's 29.1 TFLOPS, a 68-fold advantage. This boosts GH200 for AI training speed. RTX 4070 performs adequately for gaming.
Is GH200 better for LLM training than RTX 4070?▾
Yes, GH200's 4000 GB/s bandwidth and 96 GB VRAM support large-batch LLM training. RTX 4070's 504 GB/s and 12 GB limit it to small-scale experiments. Power efficiency favors RTX 4070 at 200W TDP.
Can RTX 4070 handle Stable Diffusion well?▾
RTX 4070 generates images effectively with 29.1 TFLOPS FP16 and 504 GB/s bandwidth. It outperforms in cost at $0.07 per hour for creative workflows. GH200 provides excess capacity unnecessary here.
What are the power requirements?▾
GH200 demands 900W in SXM form factor for datacenters. RTX 4070 uses 200W in PCIe, ideal for desktops. This affects deployment choices significantly.
Which is cheaper to rent, the GH200 or the RTX 4070?▾
Cloud rental prices for both the GH200 and RTX 4070 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 4070?▾
The GH200 has 96 GB of HBM3 memory. The RTX 4070 has 12 GB of GDDR6X memory.
Can I find GH200 and RTX 4070 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 4070?▾
The GH200 uses the Hopper architecture (2023) while the RTX 4070 uses Ada Lovelace (2023). The GH200 delivers 68.0x the FP16 throughput and 7.9x the memory bandwidth of the RTX 4070.