In this article
A10 suitability belongs to a verified server airflow and isolation configuration.
NVIDIA A10 is assessed here as an exact Ampere board configuration. Its published 24 GB capacity is the starting point for a workload qualification, not a measured serving or rendering result.
Exact model and memory variants
A10 provides24 GB GDDR6 in a 150 W passive full-height single-slot Ampere server card. It is not a consumer RTX board with an interchangeable cooler.
| Variant | Memory | Published board power | Cooling / format |
|---|---|---|---|
| A10 | 24 GB GDDR6 | 150 W | Passive; Full-height single-slot PCIe |
Specifications: Official product/support documentation.
LLM backend and memory budget
For24 GB Ampere, validate weight format, runtime and context. Shared graphics work needs a separate memory budget; starting two applications does not prove stable concurrent execution.
Passing the architecture requirement does not certify every model, quantization kernel or prebuilt package.
Compatibility evidence: vLLM GPU requirements.
Cycles and batch rendering
For Cycles, validate the chosen CUDA/OptiX path and complete scene execution. Physical installation and supported virtualization mode are independent conditions, not automatic consequences of graphics capabilities.
Blender 5.2 LTS GPU rendering manual.
Integration into a server or workstation
A single-slot passive card depends on the server airflow path and supported power connection. Preserve whether the test uses bare metal, a container or a virtualized device. Changing isolation can change visible memory and software requirements without changing the physical24 GB board.
A concrete qualification scenario
A mixed-use server alternates visualization and one inference worker. Establish independent model and scene controls first, then test the selected isolation arrangement. Record device visibility and free-memory baseline for each application. If concurrent work is intended, create another explicit case rather than combining two isolated successes. The resulting record documents the real server configuration and prevents a 24 GB nominal capacity from becoming an unsupported concurrency promise.
The evidence to retain
Keep an ordinary qualification record with the actual test outputs.
Identify the tested variant, software build and execution mode before entering observations. Leave unavailable measurements explicitly unknown.
The fields below separate published specifications from observed allocation and job completion, so a later operator can repeat the same case.
| Evidence field | What this profile must retain |
|---|---|
| Hardware identity | NVIDIA A10; physical variant and reported device identifier |
| Memory boundary | 24 GB published; observed free memory before and after loading |
| Inference artifact | Exact weights digest, quantization, context and offload configuration |
| Render artifact | Scene digest, renderer version, backend and denoising setting |
| System envelope | Driver, container/build digest, enclosure and cooling configuration |
| Completion evidence | Application exit status, output validity and observed memory failures |
Changing device isolation can change visible memory without changing the physical24 GB board; preserve both identities when comparing execution results.
Further reading: RAM and VRAM: which memory matters for an AI server?, A GPU inference benchmark you can trust, NVIDIA and AMD GPU catalogue.