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 200I A2 8 TOPS

Da Vinci Module 2023
VRAM
4 GB
LPDDR4X
TDP
21 W
Bandwidth
26 GB/s
memory
Da Vinci AI Core
1

Overview

The Huawei Atlas 200I A2 is an edge acceleration module built on the Ascend 310B, measuring just 82 by 60 by 7 millimetres and intended to be soldered down into a customer board. This is the lower of the two bins Huawei publishes, rated at 8 TOPS INT8 and 4 TFLOPS FP16 within 21 watts. It uses the same Ascend 310B silicon and the same single Da Vinci V300 AI core as the 20 TOPS bin but at a lower clock, which Huawei does not publish for the AI core although it does show the host CPU dropping from 1.6 GHz to 1.0 GHz across four TaiShan V200M cores. Memory is 4 GB of LPDDR4X at 25.6 GB/s and the media block handles 20 channels of 1080p30 decode.

Performance Metrics

Peak theoretical throughput by precision type

PrecisionBitsPeak TFLOPSEfficiency
INT8 8 8.0 0.381 TFLOPS/W
FP16 16 4.0 0.190 TFLOPS/W
FP16 Efficiency
0.190 TFLOPS/W
4.0 TFLOPS / 21W

Power Specifications

TDP

21 W

Max Power

21 W

Power Connector

PCIe Slot

Cooling

Air

Memory Specifications

Capacity

4 GB

Type

LPDDR4X

Bandwidth

25.6 GB/s

Interface

--

Hardware & Design

Form Factor

Module

Architecture

Da Vinci

Process Node

--

Launch Year

2023

Variant

8 TOPS

Market Segment

Professional

Full Specifications

Compute Engine
Da Vinci AI Core 1
Memory
VRAM 4 GB
Memory Type LPDDR4X
Bandwidth 26 GB/s
Power & Thermal
TDP 21 W
Max Board Power 21 W
Enterprise Features
Compute APIs CANN, MindSpore, MindX, ACL
Physical & Media
Card Length 82 mm
General
Form Factor Module
Architecture Da Vinci
Launch Year 2023

Documentation & Resources

Common Use Cases

General Compute AI/ML Workloads Data Processing

The Huawei Atlas 200I A2 is optimized for high-performance computing tasks with Da Vinci architecture delivering high TFLOPS of compute power.

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