Specifications Compared
| Spec | H100 | RTX-3090 |
|---|---|---|
| TDP | 700W | 350W |
| VRAM | 80-94 GB | 24 GB |
| CUDA Cores | 16,896 | 10,496 |
| Memory Type | HBM3 | GDDR6X |
| Architecture | Hopper | Ampere |
| Form Factors | SXM5, PCIe, NVL | PCIe |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | NVLink |
| Tensor Cores | 528 | 328 |
| FP8 Performance | 3,958 TFLOPS | |
| FP16 Performance | 1,979 TFLOPS | 35.6 TFLOPS |
| FP32 Performance | 67 TFLOPS | 35.6 TFLOPS |
| FP64 Performance | 34 TFLOPS | |
| INT8 Performance | 3,958 TOPS | |
| Memory Bandwidth | 3,350 GB/s | 936 GB/s |
Performance Analysis
Compute throughput defines key differences in AI workflows: the H100's 1979 TFLOPS FP16 dwarfs the RTX 3090's 35.6 TFLOPS, accelerating model training by orders of magnitude in half-precision formats common to deep learning. For FP32 operations, the H100 delivers 67 TFLOPS versus 35.6 TFLOPS, nearly doubling single-precision performance for scientific simulations or legacy code. The H100's FP8 capability at 3958 TFLOPS further optimizes inference for quantized large language models.
Memory bandwidth profoundly impacts practicality: 3350 GB/s on the H100 supports massive batch sizes and models exceeding 24 GB VRAM limits of the RTX 3090's 936 GB/s setup. This allows training billion-parameter LLMs without splitting across devices, reducing overhead. Higher TDP of 700 W on the H100 versus 350 W demands robust cooling but enables sustained peak performance in clusters via NVLink and PCIe 5.0 interconnects.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 QuantaCloud Partner | H100 32–1024+ GPUs · InfiniBand | ∞ | Custom configs | Multiple DCs | Reserved / cluster Get a quote in 24h | Available | ||
 Nebius | NVIDIA H100 SXM5 80GB VRAM | 80GB | 16 vCPU 200GB RAM | 🌍Europe | $2.15/GPU/hr | |||
 Vast.ai | NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 126GB RAM 1457GB Storage | Netherlands | $2.20/GPU/hr | Available | ||
 Denvr | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 1024GB RAM 22800GB Storage | Virginia | $2.30/GPU/hr $18.40/hr total (8×) | |||
 CoreWeave | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.44/GPU/hr $19.51/hr total (8×) | |||
 Cirrascale | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 192 vCPU 2048GB RAM 39738GB Storage | United States | $2.49/GPU/hr $19.92/hr total (8×) |
RTX 3090
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
Vast.ai | 8×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 64 vCPU 472GB RAM 2104GB Storage | Finland | $0.24/GPU/hr $1.92/hr total (8×) | Available | ||
Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 252GB RAM 1373GB Storage | Finland | $0.24/GPU/hr $0.96/hr total (4×) | Available | ||
Vast.ai | 2×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 96 vCPU 63GB RAM 431GB Storage | Czechia | $0.25/GPU/hr $0.49/hr total (2×) | Available | ||
Vast.ai | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 24 vCPU 31GB RAM 170GB Storage | Czechia | $0.25/GPU/hr | Available | ||
Vast.ai | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 96 vCPU 31GB RAM 190GB Storage | Czechia | $0.25/GPU/hr | Available |
QuantaCloud
Comparing H-series providers? We broker across all of them.
Most Hopper capacity is sold out through Q3 2026. If you need 16+ GPUs reserved or a cluster in the next 90 days, we quote remaining H-series or B300 inventory at partner rates — one quote, 24h turnaround.
When to Choose the H100
The H100 excels in enterprise-scale AI training and inference where VRAM exceeds 24 GB, such as with models over 70 billion parameters fitting into its 80 to 94 GB HBM3. High memory bandwidth of 3350 GB/s supports large batch sizes, minimizing training time via 1979 TFLOPS FP16 throughput. Cloud users prioritizing speed over cost select it for production deployments across SXM5 or PCIe form factors.
When to Choose the RTX 3090
The RTX 3090 suits budget-conscious prototyping and smaller-scale ML tasks fitting within 24 GB GDDR6X VRAM, like fine-tuning models under 10 billion parameters. At $0.08 per hour starting price, it offers 35.6 TFLOPS FP16 at one-tenth the H100's rental cost, ideal for individual developers or hobbyists. Its PCIe form factor simplifies single-node setups without datacenter infrastructure.
Use Cases
The H100's 80 to 94 GB HBM3 VRAM and 1979 TFLOPS FP16 handle massive datasets and billion-parameter models without multi-GPU splitting. RTX 3090's 24 GB limits scale severely.
FP8 performance of 3958 TFLOPS and 3350 GB/s bandwidth on H100 optimize low-latency serving of large models. RTX 3090's 35.6 TFLOPS FP16 falls short for high-throughput needs.
RTX 3090 suffices for models under 24 GB at $0.08 per hour, while H100 accelerates larger ones with 67 TFLOPS FP32. Choice depends on model size and budget.
RTX 3090's 24 GB GDDR6X and 35.6 TFLOPS FP16 generate images efficiently at low $0.43 per hour average cost. H100 overkill for consumer diffusion tasks.
H100's 67 TFLOPS FP32 and PCIe 5.0 interconnect speed simulations with high precision. RTX 3090's matching 35.6 TFLOPS FP32 limits complex workloads.
Frequently Asked Questions
Is H100 much faster than RTX 3090 for AI training?▾
Yes, the H100 delivers 1979 TFLOPS FP16 compared to 35.6 TFLOPS on RTX 3090, over 55 times higher throughput. This translates to drastically reduced training times for deep learning models. VRAM of 80 to 94 GB versus 24 GB further enables larger batches.
How does H100 VRAM compare to RTX 3090?▾
H100 provides 80 to 94 GB HBM3 versus RTX 3090's 24 GB GDDR6X. This allows running models too large for the 3090 without sharding. Bandwidth of 3350 GB/s on H100 exceeds 936 GB/s significantly.
What is the price difference in cloud rentals?▾
H100 starts at $0.80 per hour with $3.14 average across 57 offers, while RTX 3090 starts at $0.08 per hour averaging $0.43 across 48 offers. RTX 3090 costs about one-tenth for similar usage time. Savings suit prototyping over production.
Can RTX 3090 handle large language models?▾
RTX 3090's 24 GB VRAM limits it to models under that threshold, unlike H100's 80 to 94 GB. FP16 of 35.6 TFLOPS suffices for inference on smaller LLMs. For 70B+ parameters, H100 is required.
H100 power consumption versus RTX 3090?▾
H100 has 700 W TDP compared to RTX 3090's 350 W. This demands datacenter power but sustains 1979 TFLOPS FP16 peaks. RTX 3090 fits consumer PSUs easily.
Which has better interconnects?▾
H100 supports NVLink, PCIe 5.0, and InfiniBand for multi-GPU scaling, beyond RTX 3090's NVLink and PCIe. This excels in clusters. Single-node use sees minimal difference.
Which is cheaper to rent, the H100 or the RTX 3090?▾
Cloud rental prices for both the H100 and RTX 3090 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 3090?▾
The H100 has 80 to 94 GB of HBM3 memory. The RTX 3090 has 24 GB of GDDR6X memory.
Can I find H100 and RTX 3090 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 3090?▾
The H100 uses the Hopper architecture (2022) while the RTX 3090 uses Ampere (2020). The H100 delivers 55.6x the FP16 throughput and 3.6x the memory bandwidth of the RTX 3090.