GPUhub
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High-end Ada Lovelace consumer GPU for local AI and gaming.
Weekly median price per GPU per hour · Get the data
By provider shows one card per company, placed where its best offer ranked. By configuration lists every offer.
What you can rent comes first: in stock, then waitlist, then not reported, then out of stock. Priced offers rank ahead of quote-only, and on-demand ahead of other billing types.
Within a group, five factors set the order:
We match the provider, its country, GPU model, form factor, billing type, availability and instance name. Matching is partial and case-insensitive. Everyday words work too, so "interruptible" finds spot and "sold out" finds out of stock.
No providers match .
Heads up: A provider's own page may quote a different figure, for example on tax, region or a promotion. A monthly-only plan shows a derived hourly rate. Verify before provisioning. More on how we price.
One RTX 4080 has 16 GB of VRAM. In practice, that's enough memory for roughly 15B parameters at 4-bit or 2B at 16-bit, assuming a 32K context. Below are some open-weight LLMs, with the estimated memory and GPUs each one needs.
| Model | Memory (INT4 / FP4) | RTX 4080s needed | Cost /hr | Cost /mo |
|---|---|---|---|---|
|
|
18 GB
|
4
|
$1.40
|
$1,008
|
|
|
22 GB
|
4
|
$1.40
|
$1,008
|
|
|
67 GB
|
8
|
$2.80
|
$2,016
|
|
|
178 GB
|
13
|
–
|
–
|
|
|
239 GB
|
17
|
–
|
–
|
|
|
306 GB
|
22
|
–
|
–
|
|
|
1,544 GB
|
108
|
–
|
–
|
Estimates based on the median on-demand rate. Memory is weights plus FP8 KV cache at 32K context per request (FP16/BF16 in the 16-bit column). GPU counts assume 90% of advertised VRAM is usable. No guarantee of runtime support, usable performance, or that a matching quantized build exists. Pricing methodology.
Nvidia RTX 4080 · Per GPU
| Compute · dense | |
|---|---|
| FP8 | 194.9 TFLOPS 389.8 with sparsity |
| FP16 / BF16 | 97.5 TFLOPS 195 with sparsity |
| INT8 | 389.9 TOPS 779.8 with sparsity |
| FP32 | 48.7 TFLOPS |
| Precision support | FP8FP16BF16TF32FP32INT4INT8 |
| Memory | |
|---|---|
| Capacity | 16 GB GDDR6X |
| Bandwidth | 717 GB/s |
| Bus width | 256-bit |
| ECC | No |
| Silicon | |
|---|---|
| Architecture | Ada Lovelace |
| Process | TSMC 4N |
| Transistors | 45.9 billion |
| Shader cores | 9,728 CUDA cores |
| Matrix cores | 304 Tensor cores |
| Compute units | 76 SMs |
| Fabric and host | |
|---|---|
| Host interface | PCIe 4.0 |
| Power | |
|---|---|
| Board power | 320 W |
| Cooling | Active |
Source: official Nvidia RTX 4080 datasheet.
As of November 12, 2026, the median on-demand price is $0.35 per GPU per hour across 6 providers with a priced on-demand config.
| Billing type | Configs | Median /GPU/hr | Cheapest |
|---|---|---|---|
On-demand | 13 | $0.35 | $0.24 (in stock, Lium) |
Spot | 3 | $0.11 (not verified in stock, Salad) |
No median for spot: we only show this when at least 3 providers list the GPU on that billing type.
At 720 hours per month, one RTX 4080 costs an estimated $252 at the median on-demand price. Cheapest verified in stock: $173 per month on-demand, $115 spot.
GetDeploying currently tracks RTX 4080 configs from 7 providers. The cheapest verified in-stock on-demand configs come from Lium, Salad, GPU.ai and Theta EdgeCloud. See the full price comparison above for every provider and config.
As of November 12, 2026, the median on-demand price has risen about 6% over the past 90 days to $0.35 per GPU per hour.
One RTX 4080 runs models up to roughly 15B parameters at 4-bit quantization or 2B at 16-bit, assuming a 32K context. Larger models run across multiple GPUs: the model table above shows the estimated memory and GPU count for popular open-weight LLMs.
16GB GDDR6X with Ada Lovelace FP8 support. Good consumer option for local AI development and image generation.
16GB VRAM limits model sizes. No ECC. Subject to Nvidia's consumer EULA, which may restrict data center use. For AI workloads beyond local development, consider data center GPUs.
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