Buying an FPGA for AI inference starts with a working deployment plan for the model. Logic capacity and a quoted compute figure cannot establish whether the application will meet its latency, accuracy and power targets. Evaluate the model, hardware platform and software toolchain together before freezing the component choice.
Prove that the model has a supported implementation
AMD's Vitis AI developer resources describe quantization, compilation and runtime tools for supported adaptive-computing devices. Support is specific to devices and software releases; the availability of a vendor tool does not mean that every FPGA in its catalog can deploy the same model.
Record the model framework, operator set, input dimensions and required numerical precision. Identify unsupported operations and any work that must run on a host processor. Test quantization against an appropriate evaluation dataset. A smaller implementation is useful only if the resulting accuracy still meets the application's acceptance criteria.
Select the right level of hardware integration
A bare FPGA, a system-on-module and an accelerator card create different engineering workloads. For a bare device, include configuration memory, power sequencing, clocks, external memory and board-layout requirements. For a card, verify host interfaces, runtime drivers, thermal limits and supported system configurations.
Check memory capacity and bandwidth using the model's data movement, not just its parameter count. Include input preprocessing, intermediate buffers and output handling. Verify the selected package's available transceivers and I/O resources, because devices with similar logic capacity can expose different interfaces in different packages.
Measure the deployment you intend to buy
Run the complete pipeline at the required batch size and input rate. Measure end-to-end latency, sustained throughput, power and temperature after including transfers between the host and accelerator. Distinguish kernel execution time from the latency experienced by the application.
Archive the tool version, build settings, bitstream, runtime dependencies and hardware revision with the results. Confirm the licensing and maintenance path for production builds. Before approving an alternate part or board, identify which artifacts must be rebuilt and which tests must be repeated; a similar resource count is not a migration plan.
Frequently asked questions
Can a larger FPGA run the existing bitstream unchanged?
Do not assume so. Device, package, pin assignments and platform architecture affect implementation. Follow the vendor's supported build and migration process.
Should selection be based on advertised operations per second?
No. Compare the complete application under the intended precision, batch size and data-transfer conditions.
Request FPGA or accelerator hardware with exact device codes, tool requirements and the qualified platform. Stock, price and lead time are confirmed in the quotation.