Specifications Compared
| Spec | GTX-1080 | H100 |
|---|---|---|
| TDP | 180W | 700W |
| VRAM | 8-11 GB | 80-94 GB |
| CUDA Cores | 2,560 | 16,896 |
| Memory Type | GDDR5X | HBM3 |
| Architecture | Pascal | Hopper |
| Form Factors | PCIe | SXM5, PCIe, NVL |
| Interconnect | NVLink, PCIe 5.0, InfiniBand | |
| FP16 Performance | 8.9 TFLOPS | 1,979 TFLOPS |
| FP32 Performance | 8.9 TFLOPS | 67 TFLOPS |
| Memory Bandwidth | 320 GB/s | 3,350 GB/s |
Performance Analysis
FP16 performance defines AI training efficiency: H100 NVL reaches 1979 TFLOPS, over 222 times the GTX 1080's 8.9 TFLOPS. This gap accelerates deep learning model training, where half-precision computations dominate. FP32 on H100 NVL hits 67 TFLOPS versus 8.9 TFLOPS, aiding general compute but less critical for neural nets. H100 NVL's FP8 at 3958 TFLOPS further boosts inference on quantized models. Memory bandwidth shapes real-world throughput: 3350 GB/s on H100 NVL versus 320 GB/s on GTX 1080 supports batch sizes 10 times larger, cutting iterations for large language models. GTX 1080's 8 to 11 GB VRAM limits it to small models, while H100 NVL's 80 to 94 GB handles giants without splitting. Higher 700 W TDP on H100 NVL demands robust cooling, unlike GTX 1080's 180 W efficiency.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
GTX 1080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 4×NVIDIA GeForce GTX 1080 8GB VRAM | 8GB | 0 vCPU 64GB RAM 480GB Storage | Netherlands | $0.30/GPU/hr $1.20/hr total (4×) | Available | ||
LeaderGPU | 8×NVIDIA GeForce GTX 1080 Ti 11GB VRAM | 11GB | 0 vCPU 128GB RAM 480GB Storage | Netherlands | $0.60/GPU/hr $4.80/hr total (8×) | Available |
H100 NVL
| 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 | ||
 Voltage Park | 8×NVIDIA H100 SXM5 80GB VRAM | 80GB | 208 vCPU 928GB RAM 19200GB Storage | Dallas, Texas | $1.99/GPU/hr $15.92/hr total (8×) |
When to Choose the GTX 1080
The GTX 1080 fits budget setups for light inference or Stable Diffusion at $0.30 per hour. Its 8.9 TFLOPS FP32 and 8 to 11 GB VRAM suffice for models under 7 billion parameters. Low 180 W TDP enables easy deployment in consumer clouds without high power costs.
When to Choose the H100 NVL
The H100 NVL excels in LLM training and large-scale inference with 1979 TFLOPS FP16 and 80 to 94 GB VRAM. Its 3350 GB/s bandwidth supports massive batches for faster convergence. NVLink interconnects scale multi-GPU clusters, unavailable on GTX 1080.
Use Cases
H100 NVL's 1979 TFLOPS FP16 and 80 to 94 GB HBM3 VRAM handle billion-parameter models efficiently. GTX 1080's 8.9 TFLOPS and 8 to 11 GB limit it to tiny datasets.
H100 NVL's 3958 TFLOPS FP8 and 3350 GB/s bandwidth serve high-throughput queries on large models. GTX 1080 struggles with VRAM constraints beyond small LLMs.
H100 NVL accelerates fine-tuning via 67 TFLOPS FP32 and vast memory for full model loading. GTX 1080 requires heavy optimization due to 8.9 TFLOPS and low bandwidth.
GTX 1080 generates images at 8.9 TFLOPS for budget users; H100 NVL speeds batches with 1979 TFLOPS FP16. Choice depends on scale and cost at $0.30 versus $2.89 per hour.
H100 NVL's 67 TFLOPS FP32 and NVLink scale simulations across nodes. GTX 1080's 8.9 TFLOPS suits single-node prototypes only.
Frequently Asked Questions
How much faster is the H100 NVL than GTX 1080 for AI training?▾
H100 NVL delivers 1979 TFLOPS FP16, over 222 times GTX 1080's 8.9 TFLOPS. This translates to drastically reduced epochs for deep learning. Bandwidth of 3350 GB/s versus 320 GB/s further amplifies gains.
What is the VRAM difference between GTX 1080 and H100 NVL?▾
GTX 1080 offers 8 to 11 GB GDDR5X; H100 NVL provides 80 to 94 GB HBM3. H100 NVL loads massive models without offloading. GTX 1080 limits to smaller datasets.
Is GTX 1080 viable for Stable Diffusion?▾
GTX 1080 runs Stable Diffusion at 8.9 TFLOPS FP32 with 8 to 11 GB VRAM for basic generations. It handles 512x512 images adequately at $0.30 per hour. Larger resolutions need H100 NVL.
What are the cloud prices for these GPUs?▾
GTX 1080 starts at $0.30 per hour across one offer. H100 NVL begins at $1.40 per hour, averaging $2.89 over nine providers. Price reflects H100 NVL's datacenter capabilities.
Does H100 NVL support FP8 precision?▾
H100 NVL achieves 3958 TFLOPS in FP8 for ultra-fast inference. GTX 1080 lacks FP8 support, capping at FP16/FP32 of 8.9 TFLOPS. FP8 suits quantized LLMs on H100 NVL.
Can GTX 1080 replace H100 NVL in modern workflows?▾
GTX 1080 cannot match H100 NVL's 1979 TFLOPS FP16 or 3350 GB/s bandwidth for large-scale AI. It works for prototyping at low cost. H100 NVL is essential for production.
Which is cheaper to rent, the GTX 1080 or the H100?▾
Cloud rental prices for both the GTX 1080 and H100 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 GTX 1080 have compared to the H100?▾
The GTX 1080 has 8 to 11 GB of GDDR5X memory. The H100 has 80 to 94 GB of HBM3 memory.
Can I find GTX 1080 and H100 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 GTX 1080 and the H100?▾
The GTX 1080 uses the Pascal architecture (2016) while the H100 uses Hopper (2022). The H100 delivers 222.4x the FP16 throughput and 10.5x the memory bandwidth of the GTX 1080.