The NVIDIA RTX 4000 SFF Ada is perfect for a wide range of workloads
Deploying AI based workloads on CUDO Compute is easy and cost-effective. Follow our AI related tutorials.
Available at the most cost-effective pricing
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Virtual machines
The ideal deployment strategy for AI workloads with a RTX 4000 SFF Ada.
- Up to 8 GPUs / virtual machine
- Flexible
- Network attached storage
- Private networks
- Security groups
- Images
Pricing available on request
Enterprise
We offer a range of solutions for enterprise customers.
- Powerful GPU clusters
- Scalable data center colocation
- Large quantities of GPUs and hardware
- Optimise to your requirements
- Expert installation
- Scale as your demand grows
Specifications
Browse specifications for the NVIDIA RTX 4000 SFF Ada GPU
| Starting from | Contact us for pricing |
| Architecture | NVIDIA Ada Lovelace |
| GPU Memory | 20GB GDDR6 |
| Memory Interface | 160 bit |
| Memory Bandwidth | 280 GB/s |
| Error-Correcting Code (ECC) | Yes |
| CUDA Cores | 6,144 |
| Tensor Cores | 192 (NVIDIA fourth-generation) |
| RT Cores | 48 (NVIDIA third-generation) |
| Single-Precision Performance | 19.2 TFLOPS |
| RT Core Performance | 44.3 TFLOPS |
| Tensor Performance | 306.8 TFLOPS |
| System Interface | PCIe 4.0 x16 |
| Power Consumption | Total board power: 70 W |
| Thermal Solution | Active |
| Form Factor | 2.7” H x 6.6” L, dual slot |
| Display Connectors | 4x Mini DisplayPort 1.4a |
| Max Simultaneous Displays | 4x 4096 x 2160 @ 120 Hz, 4x 5120 x 2880 @ 60 Hz, 2x 7680 x 4320 @ 60 Hz |
| Encode/Decode Engines | 2x encode, 2x decode (+AV1 encode and decode) |
| VR Ready | Yes |
| Graphics APIs | DirectX 12, Shader Model 6.6, OpenGL 4.6, Vulkan 1.3 |
| Compute APIs | CUDA 11.6, OpenCL 3.0, DirectCompute |
| NVIDIA NVLink | No |
Ideal uses cases for the NVIDIA RTX 4000 SFF Ada GPU
Explore uses cases for the NVIDIA RTX 4000 SFF Ada including AI & deep learning, Scientific & simulation, Professional workstations.
AI & deep learning
Engineers and data scientists leverage the RTX 4000 SFF to train complex deep learning models. Its HPC power delivers unparalleled performance, enabling organizations to train neural networks faster, more efficiently and at lower costs.
Scientific & simulation
The RTX 4000 SFF plays a crucial role in scientific research and simulations. Its immense parallel processing power makes it a perfect choice for solving complex mathematical equations and running simulations in physics, chemistry, engineering and other scientific domains.
Professional workstations
Architects, designers, and engineers integrate the RTX 4000 SFF into their workstations to accelerate 3D modeling, rendering, and CAD (Computer-Aided Design). The RTX 4000 SFF seamlessly renders lifelike graphics, ensuring accurate simulation results and greater performance at an incredibly affordable price.
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AMD MI250/300
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We're proud to be an NVIDIA preferred partner for compute, offering the latest GPUs and high-performance computing solutions.
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