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Consumer GPU · Ampere

RTX 3080 rental from €0.17/h

Renting an NVIDIA GeForce RTX 3080 on VRAMfarm costs from €0.17 an hour. It is a consumer card on the Ampere architecture (2020) with 10 GB of GDDR6X memory: fast, but 10 GB limits it to SD 1.5 and models up to 7B in 4-bit. You pay by the minute from your balance, with no subscription.

To launch, your balance must cover one hour of the machine. You are billed by the minute for actual use.

10 GBGDDR6X memory
760 GB/smemory bandwidth
≈29.8TFLOPS FP32
320 WTDP
A graphics card taken apart: shroud, fans, heatsink and board floating in a row

What the RTX 3080 is good for

LLM inference

10 GB holds a model of up to about 4B parameters in FP16 and up to 15B in 4-bit, for example 13–14B models such as Qwen 2.5 14B and Phi-4. The memory bandwidth of 760 GB/s sets how fast tokens are generated.

Which LLMs fit in the 10 GB of the RTX 3080
4-bit, fitsFP16, fitsnot enough memory
Llama 3.1 8B4-bit · 6 GB ≈95 tok/s
Llama 3.1 8BFP16 · 18 GB does not fit
Qwen 2.5 14B4-bit · 10 GB ≈54 tok/s
Qwen 2.5 14BFP16 · 31 GB does not fit
Qwen 2.5 32B4-bit · 22 GB does not fit
Qwen 2.5 32BFP16 · 71 GB does not fit
Llama 3.3 70B4-bit · 47 GB does not fit
Llama 3.3 70BFP16 · 154 GB does not fit
Memory for the model weights with about 10% headroom for context. Speed is for a single request at 760 GB/s of memory bandwidth; with parallel requests in vLLM the total throughput is several times higher. Models that do not fit run on several cards.

Image generation

Good for Stable Diffusion 1.5 and light ComfyUI pipelines.

Training and fine-tuning

LoRA fine-tuning of small models, experiments and training compact networks.

Rendering

Blender Cycles, Octane and Redshift: 29.8 TFLOPS FP32 and 10 GB of memory for your scenes.

Rental cost by period

PeriodCost
1 hour€0.17
A day (24 hours)€4
A week€29
A month (720 hours)€122

Prices updated 12 November 2026. While the page is open we show the price of the cheapest reliable machine available in the catalogue. Prices are in euros. How VAT applies to your account will be shown at checkout.

Similar GPUs

  • RTX 4060 Ti: 6% cheaper, 6 GB more memory, FP32 ≈ 22.1 vs 29.8 TFLOPS.
  • RTX 3090: 76% more expensive, 14 GB more memory, FP32 ≈ 35.6 vs 29.8 TFLOPS.
  • RTX A4000: 6% more expensive, 6 GB more memory, FP32 ≈ 19.2 vs 29.8 TFLOPS.

How to rent the RTX 3080

  1. Sign up and top up your balance from €10. To launch, your balance must cover at least one hour of the machine.
  2. In the dashboard, click Rent a GPU, choose what to run (a ready-made app, PyTorch with Jupyter, vLLM or your own Docker image), then the RTX 3080 and a machine.
  3. The server is usually ready in 2–5 minutes. When you’re done, click Stop and billing stops. If you will need your models and results again, click Save and stop: /workspace is kept for €0.03 per GB per month and comes back on your next server.
A gaming PC with a triple-fan graphics card, connected to a laptop

Rental questions

How much does RTX 3080 rental cost?

From €0.17 an hour. Billing is per minute, with a minimum charge of 15 minutes per launch. To launch, your balance must cover one hour of the machine; the rest stays on your balance. Prices updated 12 November 2026.

Which AI models can I run on this card?

10 GB holds an LLM of up to about 4B parameters in FP16 or up to 15B in 4-bit, for example 13–14B models such as Qwen 2.5 14B and Phi-4.

How do I access the rented GPU?

The server is usually ready 2–5 minutes after launch. Ready-made apps for images, video and chat open with a button in the dashboard, and for your own code you get SSH and Jupyter. Developers can choose PyTorch with Jupyter, vLLM, an empty ComfyUI or their own Docker image.

How do I pay?

Top up your balance in euros by card or SEPA transfer, from €10. Payments go through a payment provider that we will announce before launch. VAT, where it applies, is shown at checkout.

How does the RTX 3080 compare with similar cards?

RTX 4060 Ti: 6% cheaper, 6 GB more memory, FP32 ≈ 22.1 vs 29.8 TFLOPS. RTX 3090: 76% more expensive, 14 GB more memory, FP32 ≈ 35.6 vs 29.8 TFLOPS. RTX A4000: 6% more expensive, 6 GB more memory, FP32 ≈ 19.2 vs 29.8 TFLOPS.

What happens to my data after I stop?

The server disk is wiped when you stop. If you need your models and results, click Save and stop: we keep /workspace for €0.03 per GB per month, and your next server gets it automatically. Saving does not work yet for custom Docker images.

Launch the RTX 3080

Available machines with an hourly price, billed by the minute from your balance.