Specifications Compared
| Spec | H100 | RTX-3060 |
|---|---|---|
| TDP | 700W | 170W |
| VRAM | 80-94 GB | 12 GB |
| CUDA Cores | 16,896 | 3,584 |
| Memory Type | HBM3 | GDDR6 |
| Architecture | Hopper | Ampere |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| Tensor Cores | 528 | 112 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 12.7 TFLOPS |
| FP32 Performance | 67 TFLOPS | 12.7 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 360 GB/s |
Performance Analysis
The H100's FP16 performance of 1979 TFLOPS vastly outpaces the RTX 3060's 12.7 TFLOPS, enabling faster model training and inference in low-precision formats common to deep learning. Its FP32 throughput of 67 TFLOPS exceeds the RTX 3060's 12.7 TFLOPS, but the pronounced FP16-to-FP32 ratio on the H100 signals optimization for AI tasks over general compute. In practice, this means the H100 accelerates large-scale neural network training by orders of magnitude, reducing epochs from days to hours.
Memory bandwidth defines batch size feasibility: the H100's 3350 GB/s supports massive batches for stable diffusion or LLM training, minimizing overhead from data loading, whereas the RTX 3060's 360 GB/s limits it to smaller batches prone to out-of-memory errors beyond 12 GB VRAM. For inference, the H100's FP8 capability at 3958 TFLOPS further boosts throughput for high-volume serving, unavailable on the RTX 3060. These specs translate to the H100 handling enterprise-scale models, while the RTX 3060 suits lightweight prototyping.
Power draw underscores efficiency: the H100's 700W TDP demands robust cooling but delivers density for clusters, contrasting the RTX 3060's 170W for edge deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Hyperstack | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 124 vCPU 720GB RAM 3300GB Storage | Canada | $1.90/GPU/hr $7.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA H100 PCIe 80GB VRAM | 80GB | 60 vCPU 360GB RAM 1600GB Storage | Canada | $1.90/GPU/hr $3.80/hr total (2×) | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.90/GPU/hr $15.20/hr total (8×) | Available | ||
Hyperstack | NVIDIA H100 PCIe 80GB VRAM | 80GB | 28 vCPU 180GB RAM 850GB Storage | Canada | $1.90/GPU/hr | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.95/GPU/hr $15.60/hr total (8×) | Available |
RTX 3060
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 36 vCPU 31GB RAM 862GB Storage | Texas | $0.23/GPU/hr | Available | ||
Vast.ai | 2×NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 24 vCPU 55GB RAM 1940GB Storage | Texas | $0.23/GPU/hr $0.45/hr total (2×) | Available | ||
Vast.ai | 2×NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 128 vCPU 168GB RAM 715GB Storage | Texas | $0.23/GPU/hr $0.45/hr total (2×) | Available | ||
Vast.ai | 2×NVIDIA GeForce RTX 3060 12GB VRAM | 12GB | 64 vCPU 126GB RAM 3050GB Storage | Texas | $0.23/GPU/hr $0.45/hr total (2×) | Available |
When to Choose the H100
The H100 excels in demanding AI workloads requiring vast memory and compute. Large language model training benefits from its 80-94 GB HBM3 VRAM and 1979 TFLOPS FP16, accommodating models with billions of parameters without splitting. High-throughput inference leverages 3958 TFLOPS FP8 and 3350 GB/s bandwidth for real-time applications at scale.
Enterprise users prioritize the H100 for its NVLink and InfiniBand interconnects, enabling multi-GPU clusters across 57 cloud offers averaging $3.14 per hour.
When to Choose the RTX 3060
The RTX 3060 fits budget-conscious prototyping and small-scale tasks. Its 12 GB GDDR6 VRAM and 12.7 TFLOPS FP16/FP32 suffice for fine-tuning compact models or running stable diffusion at 360 GB/s bandwidth. Low pricing from $0.03 per hour across 12 offers makes it ideal for hobbyists or initial experiments.
Power-sensitive environments favor its 170W TDP and PCIe form factor for easy integration without data center infrastructure.
Use Cases
The H100's 80-94 GB HBM3 VRAM and 1979 TFLOPS FP16 support training massive LLMs with large batch sizes via 3350 GB/s bandwidth. The RTX 3060's 12 GB limits it to tiny models.
H100's 3958 TFLOPS FP8 and high bandwidth enable high-throughput serving of large LLMs. RTX 3060 struggles with memory constraints beyond basic queries.
Small fine-tuning tasks fit RTX 3060's 12 GB VRAM at low cost, but H100 accelerates larger datasets with 67 TFLOPS FP32. Choice depends on model size.
RTX 3060's 12.7 TFLOPS and 12 GB GDDR6 handle image generation efficiently at $0.07 per hour average. H100 overkill for single-user workflows.
H100's 67 TFLOPS FP32 and NVLink interconnects scale simulations across nodes. RTX 3060's 12.7 TFLOPS suits only modest computations.
Frequently Asked Questions
What is the VRAM difference between H100 and RTX 3060?▾
The H100 provides 80-94 GB HBM3 VRAM, far exceeding the RTX 3060's 12 GB GDDR6. This enables the H100 to load massive datasets, while the RTX 3060 faces limits in large model training.
How do H100 and RTX 3060 compare in cloud pricing?▾
H100 starts at $0.80 per hour with an average of $3.14 per hour across 57 offers. RTX 3060 begins at $0.03 per hour averaging $0.07 per hour over 12 offers, favoring budget tasks.
Which has higher FP16 performance: H100 or RTX 3060?▾
H100 delivers 1979 TFLOPS FP16, over 150 times the RTX 3060's 12.7 TFLOPS. This gap accelerates AI training significantly on the H100.
What are the power requirements for H100 vs RTX 3060?▾
H100 has a 700W TDP suitable for data centers, compared to RTX 3060's 170W for consumer setups. Higher TDP correlates with H100's superior compute density.
Can RTX 3060 handle LLM inference like H100?▾
RTX 3060 manages small LLMs with 12 GB VRAM but lacks H100's 3958 TFLOPS FP8 and 3350 GB/s bandwidth for high-volume or large-model inference.
What architectures power H100 and RTX 3060?▾
H100 uses Hopper from 2022 optimized for AI, while RTX 3060 employs Ampere from 2021 geared toward gaming and general compute. Hopper provides advanced tensor cores absent in Ampere.
Which is cheaper to rent, the H100 or the RTX 3060?▾
Cloud rental prices for both the H100 and RTX 3060 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 H100 have compared to the RTX 3060?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 3060 has 12 GB of GDDR6 memory.
Can I find H100 and RTX 3060 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 H100 and the RTX 3060?▾
The H100 uses the Hopper architecture (2022) while the RTX 3060 uses Ampere (2021). The H100 delivers 155.8x the FP16 throughput and 9.3x the memory bandwidth of the RTX 3060.