NVIDIA RTX 4080 SUPER cloud GPU rental
Rent an NVIDIA RTX 4080 SUPER cloud GPU from $0.303 per hour with 16 GB of GDDR6X at 736 GB/s of memory bandwidth. FastInfra bills pods per minute with no commitment, so a one-hour experiment costs $0.303 and you stop paying the moment you delete the pod. Run 1 to 4 GPUs per pod, connect over SSH or JupyterLab, and see the exact price before you deploy.
Prices synced November 3, 2026 · billed per minute
RTX 4080 SUPER specs and pricing
The NVIDIA RTX 4080 SUPER is a consumer Ada Lovelace GPU with 16 GB of GDDR6X at 736 GB/s of memory bandwidth. On FastInfra it is a good fit for small-model inference, embeddings, prototyping and CI workloads. As a rule of thumb, one RTX 4080 SUPER holds the weights of a model of about 6B parameters at 16-bit precision, or about 25B with 4-bit quantization, after leaving room for the KV cache.
The RTX 4080 SUPER runs on the Value tier, lower-cost community hosts, at $0.303 per GPU-hour.
RTX 4080 SUPER price per hour by GPU count
Live FastInfra prices per pod-hour. Pods bill per minute, so you pay only for the minutes a pod exists.
| Pod size | Total VRAM | Value / hr | Month (730 h, lowest) |
|---|---|---|---|
| 1× RTX 4080 SUPER | 16 GB | $0.303 | $221 |
| 2× RTX 4080 SUPER | 32 GB | $0.606 | $442 |
| 4× RTX 4080 SUPER | 64 GB | $1.21 | $885 |
What an RTX 4080 SUPER costs over time
One GPU at the lowest on-demand rate ($0.303/hr).
| Duration | On-demand |
|---|---|
| 1 hour | $0.303 |
| 8-hour working day | $2.42 |
| 24 hours | $7.27 |
| 1 week (168 hours) | $50.90 |
| 1 month (730 hours) | $221 |
Which LLMs fit on the RTX 4080 SUPER?
GPUs needed to hold the model weights with about 20% of VRAM left for the KV cache. Rule of thumb only: long contexts and big batches need more.
| Model size | Examples | FP16 / BF16 | 8-bit | 4-bit |
|---|---|---|---|---|
| 7–8B | Llama 3.1 8B, Qwen3 8B, Mistral 7B | 2 GPUs | 1 GPU | 1 GPU |
| 12–14B | Gemma 3 12B, Qwen3 14B, Phi-4 | 4 GPUs | 2 GPUs | 1 GPU |
| 27–32B | Gemma 3 27B, Qwen3 32B | Needs more GPUs | 4 GPUs | 2 GPUs |
| 70B | Llama 3.3 70B | Needs more GPUs | Needs more GPUs | 4 GPUs |
| 120B | GPT-OSS 120B | Needs more GPUs | Needs more GPUs | Needs more GPUs |
Best for
Small-model inference, embeddings, prototyping and CI workloads.
About the Ada Lovelace architecture
Ada Lovelace GPUs have fourth-generation Tensor Cores with FP8 support and large L2 caches. They are a cost-efficient choice for inference, Stable Diffusion and ComfyUI, video generation, rendering and LoRA fine-tuning, where memory capacity matters more than the multi-GPU interconnect of datacenter parts.
Only need inference?
If you want to call an open model such as Llama, Qwen, DeepSeek or GPT-OSS rather than manage a server, the pay-per-token inference API is often cheaper than keeping a GPU busy around the clock. It is OpenAI-compatible and uses the same account and wallet as your pods. Browse every model with live prices.
RTX 4080 SUPER vs similar GPUs
Live lowest on-demand price per GPU-hour, and price per GB of VRAM.
| GPU | VRAM | Architecture | From / hr | Per GB-hr |
|---|---|---|---|---|
| RTX 4080 SUPER (this page) | 16 GB | Ada Lovelace | $0.303 | $0.019 |
| NVIDIA RTX A4000 | 16 GB | Ampere | $0.184 | $0.012 |
| NVIDIA Tesla V100 | 16 GB | Volta | $0.206 | $0.013 |
| NVIDIA V100 SXM2 | 16 GB | Volta | $0.249 | $0.016 |
| NVIDIA RTX 2000 Ada | 16 GB | Ada Lovelace | $0.26 | $0.016 |
| NVIDIA RTX 4080 | 16 GB | Ada Lovelace | $0.292 | $0.018 |
| NVIDIA RTX 5080 | 16 GB | Blackwell | $0.422 | $0.026 |
RTX 4080 SUPER rental — frequently asked questions
How much does it cost to rent an NVIDIA RTX 4080 SUPER per hour?
$0.303 per GPU-hour on demand. Billing is per minute while the pod exists, so 24/7 use for a 730-hour month costs about $221 per GPU at the lowest on-demand rate. Prices sync from live capacity and are shown before you deploy.
How much VRAM does the NVIDIA RTX 4080 SUPER have?
16 GB of GDDR6X at 736 GB/s of memory bandwidth. The chip is rated at up to 320 W. A pod with 4 GPUs gives 64 GB of combined VRAM for tensor- or pipeline-parallel workloads.
What size LLM can I run on an NVIDIA RTX 4080 SUPER?
Roughly 6B parameters at FP16 or BF16, 12B at 8-bit and 25B at 4-bit on a single GPU, reserving about 20% of VRAM for the KV cache and activations. Mixture-of-experts models need memory for all experts, not only the active ones. Long contexts and large batches need more headroom.
Is the NVIDIA RTX 4080 SUPER billed per hour or per minute?
Per minute. The hourly rate is divided by 60 and charged for every minute the pod exists. Attached volumes bill per GB-month and continue while a pod is stopped; delete the pod to stop all charges. There is no minimum term or reservation fee.
How do I rent an NVIDIA RTX 4080 SUPER on FastInfra?
Create an account, add prepaid credit, open the GPU configurator and choose the RTX 4080 SUPER, the tier, the GPU count, a container template and storage. The configurator shows the hourly and monthly price, then deploys a pod you reach over SSH or JupyterLab within minutes.
Can I rent multiple RTX 4080 SUPER GPUs in one pod?
Yes, up to 4 per pod. The price scales linearly: 4 GPUs cost $1.21 per hour on Value.
Is there a cheaper GPU than the RTX 4080 SUPER with the same VRAM?
Yes. The NVIDIA RTX A4000 has 16 GB and starts at $0.184 per hour. It differs in architecture (Ampere), memory bandwidth and multi-GPU interconnect, so compare throughput for your workload before switching.
Deploy an RTX 4080 SUPER in minutes
Price the exact pod, storage and template in the configurator, add credit, and connect over SSH or JupyterLab. Billed per minute, no commitment.