AI acceleration
Tensor Core architecture is designed for modern training and inference workloads, including transformer and generative-AI pipelines.
NVIDIA A30 Tensor Core GPU 24GB
$1,080
NVIDIA A30 Tensor Core GPU 24GB is an enterprise accelerator built on NVIDIA Ampere for enterprise AI inference, training and HPC. It combines 24 GB HBM2 with 933 GB/s memory bandwidth-class performance and a PCIe deployment format, making it suitable for dense AI, accelerated analytics and high-performance computing platforms.
Explore Related
Related products, categories and research.
NVIDIA L40S Graphics Card, 48GB GDDR6 ECC with 864GB/s Memory Bandwith, 1466 TFLOPS Tensor Performance, 18176 CUDA Cores, Passive Thermal, PCIe Gen4, 4x DisplayPort 1.4a | L40SNVIDIA RTX 2000 Ada Generation Graphics Card, 16GB GDDR6 128-Bit Memory, 224 GB/s Memory Bandwidth, 2816 CUDA Cores, ECC, 4x Mini DisplayPort 1.4a, 8x PCIe 4.0 Interface | 900-5G192-2240-000NVIDIA DGX Vera Rubin NVL72NVIDIA Vera Rubin NVL72
Enterprise accelerated computing
NVIDIA A30 Tensor Core GPU 24GB
NVIDIA A30 Tensor Core GPU 24GB is an enterprise accelerator built on NVIDIA Ampere for enterprise AI inference, training and HPC. It combines 24 GB HBM2 with 933 GB/s memory bandwidth-class performance and a PCIe deployment format, making it suitable for dense AI, accelerated analytics and high-performance computing platforms.
24 GBAccelerator memory
933 GB/sMemory bandwidth
EnterpriseDeployment class
Product overview
Built around the real deployment workflow
This product page is structured for buyers comparing performance, memory capacity, software support and physical compatibility. The named board should be matched to the target workload first, then checked for power, cooling, slot clearance and driver/application support.
NVIDIA A30 Tensor Core GPU 24GB is an enterprise accelerator built on NVIDIA Ampere for enterprise AI inference, training and HPC. It combines 24 GB HBM2 with 933 GB/s memory bandwidth-class performance and a PCIe deployment format, making it suitable for dense AI, accelerated analytics and high-performance computing platforms.
Key features
What matters when evaluating NVIDIA A30 Tensor Core GPU 24GB
Core platform capabilities and practical deployment considerations for the named model.
High-bandwidth memory
24 GB HBM2 provides capacity for large models, datasets and memory-intensive accelerated workloads.
Platform integration
PCIe format is intended for validated enterprise server platforms rather than consumer desktop systems.
CUDA ecosystem
Broad support for NVIDIA CUDA libraries, AI frameworks and accelerated data-science software.
Datacenter operations
Designed for managed server environments where thermal, power, firmware and driver compatibility are engineered as a complete platform.
Scale-out readiness
Suitable for high-speed networked clusters when paired with validated server, fabric and orchestration infrastructure.
Applications
Where this platform fits
Representative professional use cases. Final suitability depends on the exact configuration and application requirements.
Generative AI
Training and serving large language, multimodal and foundation models.
AI inference
High-throughput enterprise inference and model-serving pipelines.
HPC
Scientific simulation, engineering analysis and accelerated research computing.
Data analytics
GPU-accelerated analytics, vector search and data-processing workloads.
Research clusters
Multi-node research and institutional computing environments.
Private AI infrastructure
On-premises accelerated platforms with enterprise control over data and models.
Technical specifications
Product and configuration data
Use these model-level specifications for evaluation, then confirm the exact SKU, revision and ordered configuration before deployment.
- GPU architecture
- NVIDIA Ampere
- Accelerator memory
- 24 GB HBM2
- Memory bandwidth
- 933 GB/s
- Deployment interface
- PCIe
- Primary workload
- enterprise AI inference, training and HPC
- Software ecosystem
- NVIDIA CUDA, enterprise AI and accelerated-computing software stacks
- System requirements
- Compatible server platform, validated power delivery, airflow/cooling and supported firmware/driver stack
Package & configuration
Specify the complete deployment, not only the model number
The final quotation should make the exact configuration explicit so procurement, installation and acceptance teams are working from the same bill of materials.
Core product
Named graphics card / accelerator in the quoted manufacturer and model configuration.
- Exact manufacturer and model/SKU
- Configuration and region-specific items
- Condition, packaging and included standard accessories confirmed in quotation
Configuration confirmation
Exact board revision, packaging, accessories, connector/adaptor bundle, regional documentation and warranty terms are confirmed with the quotation.
- Installation/deployment prerequisites
- Optional accessories and workflow components
- Support, training or service requirements where applicable
FAQ
Buyer questions
Practical checks to complete before the final purchase order.
Will NVIDIA A30 Tensor Core GPU 24GB fit my workstation or desktop?
Confirm card length, height, slot thickness, motherboard clearance, power connectors and PSU capacity for the exact board revision before ordering.
Are the GPU specifications the same across partner cards?
Core GPU architecture and reference processor/memory specifications are shared at the GPU-family level, but board partners can change clocks, cooler design, dimensions, outputs and power limits.
Can this GPU be used for AI workloads?
Yes, within the capabilities of the GPU and supported software stack. Model size and performance depend on VRAM capacity, compute support, drivers, framework versions and workload precision.
What should I verify for a professional application?
Check application certification, driver requirements, VRAM capacity, display needs and any vendor-specific support requirements before deploying the card in a production workstation.
What is included with the quoted GPU?
The exact accessory bundle, packaging, regional documentation and warranty/service terms should be confirmed on the quotation for the named SKU or revision.
NVIDIAManufacturer
Manufacturer context
NVIDIA
NVIDIA develops accelerated-computing platforms used across AI, scientific computing, visualization and data-center workloads. The named accelerator should be deployed only in a compatible, validated server configuration.
AI Robot Supplier
Procurement support for technical equipment
Use the quotation stage to lock the exact model, configuration, compatibility requirements and delivery package before shipment.
Confirm the named SKU/revision and required accessories before order release.
Match the equipment to workload, facility, software and integration requirements.
Align packing, insurance, destination requirements and receiving/site readiness.
Keep the quotation, BOM and available product documentation aligned for deployment.
Related products
Compare NVIDIA A30 Tensor Core GPU 24GB with related equipment
Explore the Graphic Cards catalogue, browse related products, or contact AI Robot Supplier for model, configuration and delivery checks. Manufacturer-level product-family information is available from NVIDIA.
Next step
Need the exact NVIDIA A30 Tensor Core GPU 24GB configuration?
Send the intended use, destination and required configuration so the quotation can be matched to the real deployment.
