Sold and deployed almost entirely inside mainland China. Huawei is on the US Entity List and Ascend silicon is export-controlled wherever it is located, so it cannot be rented from any provider on this site.
HU

Huawei Atlas 300V Pro

Da Vinci PCIe 2022
VRAM
48 GB
LPDDR4X
TDP
72 W
Bandwidth
205 GB/s
memory

Overview

The Huawei Atlas 300V Pro is a video analysis card built on a single Ascend 310P, and despite that positioning Huawei publishes full AI throughput for it: 140 TOPS INT8 and 70 TFLOPS FP16, identical to the Atlas 300I Pro that uses the same chip at the same 72 watts. For scale, that INT8 figure exceeds an NVIDIA T4. The differences from the 300I Pro are 48 GB of LPDDR4X rather than 24 GB, ECC support, and a much larger media block: 128 channels of 1080p30 H.264 or H.265 decode, or 16 channels of 4K60, plus 24 channels of 1080p30 encode and JPEG decode at 384 frames per second at 4K. It is a half-height half-length PCIe 4.0 x16 card.

Performance Metrics

Peak theoretical throughput by precision type

PrecisionBitsPeak TFLOPSEfficiency
INT8 8 140.0 1.944 TFLOPS/W
FP16 16 70.0 0.972 TFLOPS/W
FP16 Efficiency
0.972 TFLOPS/W
70.0 TFLOPS / 72W

Power Specifications

TDP

72 W

Max Power

72 W

Power Connector

PCIe Slot

Cooling

Air

Memory Specifications

Capacity

48 GB

Type

LPDDR4X

Bandwidth

204.8 GB/s

Interface

--

Hardware & Design

Form Factor

PCIe

Architecture

Da Vinci

Process Node

--

Launch Year

2022

Variant

Standard

Market Segment

Professional

Chiplets

1

Full Specifications

Chip Design
Chiplets 1
Memory
VRAM 48 GB
Memory Type LPDDR4X
Bandwidth 205 GB/s
Interconnect & I/O
PCIe 4.0 x16
Power & Thermal
TDP 72 W
Max Board Power 72 W
Enterprise Features
ECC Memory Yes
Compute APIs CANN, MindSpore, MindX, PyTorch (torch_npu), ACL
Physical & Media
Card Length 169.5 mm
General
Form Factor PCIe
Architecture Da Vinci
Launch Year 2022

Documentation & Resources

Common Use Cases

General Compute AI/ML Workloads Data Processing

The Huawei Atlas 300V Pro is optimized for high-performance computing tasks with Da Vinci architecture delivering high TFLOPS of compute power.

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