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Workstation GPU · Blackwell

RTX PRO 6000 rental from €2.12/h

Renting an NVIDIA RTX PRO 6000 Blackwell on VRAMfarm costs from €2.12 an hour. It is a workstation card on the Blackwell architecture (2025) with 96 GB of GDDR7 memory: 96 GB on a single card, an alternative to the H100 for serving big models. 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.

96 GBGDDR7 memory
1,792 GB/smemory bandwidth
≈125TFLOPS FP32
600 WTDP
A workstation graphics card in front of a large field of glowing memory tiles

What the RTX PRO 6000 is good for

LLM inference

96 GB holds a model of up to about 43B parameters in FP16 and up to 145B in 4-bit, for example Llama 3.3 70B, Qwen 2.5 72B and Command R+ 104B. The memory bandwidth of 1,792 GB/s sets how fast tokens are generated.

Which LLMs fit in the 96 GB of the RTX PRO 6000
4-bit, fitsFP16, fitsnot enough memory
Llama 3.1 8B4-bit · 6 GB ≈224 tok/s
Llama 3.1 8BFP16 · 18 GB ≈67 tok/s
Qwen 2.5 14B4-bit · 10 GB ≈128 tok/s
Qwen 2.5 14BFP16 · 31 GB ≈38 tok/s
Qwen 2.5 32B4-bit · 22 GB ≈56 tok/s
Qwen 2.5 32BFP16 · 71 GB ≈17 tok/s
Llama 3.3 70B4-bit · 47 GB ≈26 tok/s
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 1,792 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 Flux.1 [dev] at full precision, SDXL with ControlNet and LoRA training without compromises.

Training and fine-tuning

LoRA/QLoRA fine-tuning of models up to 34B parameters and training small networks from scratch.

Rendering

Blender Cycles, Octane and Redshift: 125 TFLOPS FP32 and 96 GB of memory for your scenes.

Rental cost by period

PeriodCost
1 hour€2.12
A day (24 hours)€51
A week€356
A month (720 hours)€1,526

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

  • L40S: 50% cheaper, 48 GB less memory, FP32 ≈ 91.6 vs 125 TFLOPS.
  • A100: 31% cheaper, 16 GB less memory, FP32 ≈ 19.5 vs 125 TFLOPS.
  • RTX 5090: 64% cheaper, 64 GB less memory, FP32 ≈ 104.8 vs 125 TFLOPS.

How to rent the RTX PRO 6000

  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 PRO 6000 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 laptop with a start ring on screen, connected to a workstation with three graphics cards

Rental questions

How much does RTX PRO 6000 rental cost?

From €2.12 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?

96 GB holds an LLM of up to about 43B parameters in FP16 or up to 145B in 4-bit, for example Llama 3.3 70B, Qwen 2.5 72B and Command R+ 104B.

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 PRO 6000 compare with similar cards?

L40S: 50% cheaper, 48 GB less memory, FP32 ≈ 91.6 vs 125 TFLOPS. A100: 31% cheaper, 16 GB less memory, FP32 ≈ 19.5 vs 125 TFLOPS. RTX 5090: 64% cheaper, 64 GB less memory, FP32 ≈ 104.8 vs 125 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 PRO 6000

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