Which kind of GPU do you need?
Choose the GPU for the job, not the biggest number on its product page. Start with software compatibility, memory, and the result you need.
A practical selection order
- Can the software run
Supported GPU, libraries, and formats
- Does the full job fit
Working memory and communication needs
- Does the system meet the target
Measured performance, cooling, support, and cost
Check the constraints in order
Will the application run on this GPU? Does its full working set fit? Can it meet the performance target? Can the complete server be powered, cooled, and supported?
Consumer, workstation, and data-center products have different deployment requirements. A passive server accelerator may depend on airflow an ordinary desktop cannot provide.
Compare complete options
The NVIDIA L4 is a documented 24 GB, 72 W design point. AMD’s MI300X platform is a very different eight-accelerator system with 192 GB per accelerator.
These are examples, not interchangeable purchases or promised application speeds. Include required software changes, support, and complete-system cost.
Try it yourself
What else would you ask about a batch job that fits in 12 GB, versus an interactive service with 100 GB of weights?
Check your answer
For both, verify software and measured performance. For the second, also establish total memory, concurrency, latency, and whether a supported multi-GPU arrangement is needed. Weights alone do not describe runtime memory.