Ampere architecture
NVIDIA A2
NVIDIA A2 is a low-profile, low-power Ampere card with 16 GB of GDDR6 — cost-conscious acceleration for inference, edge analytics and light graphics in standard servers.
- GPU memory
- 16 GB GDDR6
- Memory bandwidth
- 200 GB/s
- Max TDP
- 40–60 W
Specifications as published by NVIDIA; Tensor Core ratings shown are sparsity-accelerated figures.
Overview
Why A2 fits
Ampere architecture, entry form factor
Not every GPU workload needs a flagship part. A2 fits the long tail: small model inference, image and video analytics, document processing and test environments, in a half-height single-slot card that slots into almost any server. With 16 GB of memory, it comfortably covers models that larger cards would only waste capacity on.
It is our typical answer for pilot projects and wide-but-light deployments — many servers, modest GPU footprint each. Capacity is partner-sourced; configurations are confirmed per engagement.
Specifications
A2 technical specifications
Published figures for the accelerator, followed by the variant and configuration caveats that apply.
- Architecture
- NVIDIA Ampere
- GPU memory
- 16 GB GDDR6
- Memory bandwidth
- 200 GB/s
- Interconnect
- PCIe Gen4 x8
- Form factor
- 1-slot, low-profile
- Max TDP
- 40–60 W (configurable)
Variant & configuration note
Half-height, half-length single-slot card with a 60 W maximum power limit. Host server configuration is scoped per engagement.
Specifications describe the GPU itself as published by NVIDIA — not a fixed server configuration. Scalenta scopes complete instances (GPU count, interconnect, CPU, memory, storage) per engagement and states them in writing.
Use cases
Where A2 fits
Workload shapes this platform suits — the scoping conversation maps them to a concrete configuration.
Entry inference
Serving lightweight vision and language models where a flagship GPU would be idle most of the time.
Edge and branch analytics
Video analytics, OCR and sensors in servers with tight power, space and cost budgets.
Development and test
Giving engineers a real GPU target for CI pipelines and staging environments without reserving premium capacity.
Delivery model
Partner-sourced, scoped in writing
How GPU capacity is delivered at Scalenta — the same three commitments on every model page.
Partner-sourced capacity
Accelerator capacity is sourced through verified data center and hardware partners — no facility-ownership claims, no stock promises.
Scoped per engagement
Model, variant, GPU count, interconnect and host configuration are confirmed in writing before anything is committed.
Operated with 24/7 support
Deployments are covered by 24/7 support and SLA-backed managed services scoped to your environment.
Related GPU models
Nearby options in the catalogue
NVIDIA A30
A right-sized Ampere accelerator for teams stepping up from CPU inference or low-end GPUs into real AI capacity.
- GPU memory
- 24 GB HBM2
- Memory bandwidth
- 933 GB/s
- Max power
- 165 W
NVIDIA L4
The efficiency play: dense video processing and AI inference in a low-profile card built for many-servers, many-streams deployments.
- GPU memory
- 24 GB GDDR6
- Memory bandwidth
- 300 GB/s
- Max power
- 72 W
NVIDIA A100
A proven training-and-HPC accelerator with an 80 GB memory pool per GPU and mature tooling across the AI ecosystem.
- GPU memory
- 80 GB HBM2e
- Memory bandwidth
- 2,039 GB/s
- FP16 tensor
- 624 TFLOPS
FAQ
A2 — common questions
What can A2 realistically run?
Is A2 suitable for production or only for pilots?
Can A2 run in the same fleet as larger GPUs?
Request a GPU consultation
Talk to us about NVIDIA A2 — workload-first scoping, written findings and a proposal with clear scope. No obligation.