NVIDIA RTX 6000 Ada Generation.48 GB Pro GPU on Demand
Rent the RTX 6000 Ada.48 GB GDDR6, 18,176 CUDA cores, 568 4th-gen Tensor cores. The flagship Ada-architecture pro GPU for AI training, inference and high-end rendering. Deploy in minutes from German data centers.
Why the RTX 6000 Ada
Flagship Ada Performance
Top-end Ada Lovelace silicon.91 TFLOPS FP32, 1457 TFLOPS FP8 Tensor performance.
48 GB GDDR6 ECC
Train and fine-tune medium-large LLMs, run full SDXL pipelines, render gigantic 3D scenes.
AI Training & Inference
FP8 + bfloat16 + sparsity support.vLLM, Transformer Engine, all the optimizations work out of the box.
Pro Rendering Powerhouse
3rd-gen RT cores, full OptiX support for strong Blender, Octane, V-Ray performance.
Multi-GPU Available
Configure 1x, 2x, 4x or more in a single server, scale linearly for distributed training.
Hosted in Germany
GDPR-compliant data centers, low EU latency, no US-cloud lock-in.
What's Included
- 1× NVIDIA RTX 6000 Ada Generation (48 GB GDDR6 ECC)
- AMD EPYC vCPU cores and RAM
- Fast NVMe SSD storage
- 1× IPv4 + /64 IPv6
- Generous traffic, no overage
- Full root access, bring your own AI stack
- Multi-GPU configurations and snapshots available
RTX 6000 Ada Specs
Rent RTX 6000 Ada
RTX 6000 Ada plans from €749.99/month. Multi-GPU and longer contracts unlock significant discounts.
Frequently Asked Questions
What workloads is the RTX 6000 Ada best for?+
The 48 GB VRAM makes it ideal for fine-tuning and inference of mid-to-large LLMs (7B–70B quantized), Stable Diffusion XL pipelines, professional 3D rendering and scientific computing. For pure training of very large models from scratch, H100 / A100 are still faster.
How does it compare to the L40S?+
The RTX 6000 Ada and the L40S share the same AD102 silicon, same 48 GB GDDR6 ECC, same Tensor and RT core counts. Performance is within a few percent for most workloads. The RTX 6000 Ada is typically priced lower in cloud rentals.
Can I run multiple GPUs in one server?+
Yes.2x, 4x and larger configurations are available for distributed training and high-throughput inference.
Does it support FP8 and Transformer Engine?+
Yes. Full 4th-gen Tensor cores with FP8, BF16, and structural sparsity support. NVIDIA Transformer Engine and vLLM with FP8 KV cache work natively.