
Subscribe To Our Newsletter!
Subscribe to the newsletter to stay up to date with the latest news and most useful
Newsletter
↑
Back to Top
| Product Overview |
|---|
The Lenovo NVIDIA Tesla A2 16GB GPU professional computing card offers focused acceleration for AI inference and data analysis in a compact format. It fits neatly into Lenovo servers and delivers needed GPU power for demanding enterprise workloads without taking up excess space. |
| General Information | |
|---|---|
| Brand | Lenovo |
| Part Number | 03GX831 |
| Technical Information | |
|---|---|
| Chipset | Nvidia |
| Bus Interface | PCIe 4.0 x8 |
| Supported APIs | OpenCL, CUDA, DirectCompute |
| Output Interface | None (headless, no display outputs) |
| Memory | |
|---|---|
| Memory Size | 16GB |
| Interface | GDDR6 |
| Physical Characteristics | |
|---|---|
| Slot Width | Single-slot, Low-profile |
| Weight | 3.00 |
| Condition | Refurbished |
| Miscellaneous | |
|---|---|
| Assembly Required | Yes |
| Eco Friendly | Yes |
| Compliance Standards | WEEE, RoHS, cURus, CE, FCC, CCC, UL, TUV, cULus, CSA, cUL |
| Product Description |
|---|
The Lenovo NVIDIA Tesla A2 16GB GPU is built for accelerating complex workloads such as AI inference, data analytics, and high-performance computing applications. This card delivers efficient parallel processing power while maintaining a compact form factor, making it well-suited for server racks and data centers where space is limited. Often found in enterprise environments, research labs, and cloud infrastructure, it supports professionals who require reliable GPU acceleration for demanding computational tasks. IT teams and data scientists benefit from its balance of performance and energy efficiency. Key Features
This GPU is typically integrated into Lenovo server systems powering AI workloads and intensive compute jobs. By offering solid performance in a compact package, it helps organizations tackle complex data processing tasks without requiring oversized hardware. Its role in accelerating machine learning inference and scientific simulations makes it a practical choice where computational density and reliability matter most. |