Huawei · Server Machines

Huawei Atlas 800 Training Server (Model 9000)

New Model: Atlas 800 9000

4U flagship AI training server with 8× Huawei Ascend 910B NPUs fully interconnected over HCCS and quad Kunpeng 920 ARM hosts — built for large-scale AI/LLM training on the CANN / MindSpore stack. High-capacity DDR4, local NVMe and up to 8× 200 Gb RoCE for scale-out clusters. NPU, memory, storage and fabric are configurable.

Build production AI/ML and LLM training infrastructure on the genuine Huawei Atlas 800 Training Server (Model 9000) — GPU/accelerator-dense compute supplied in Pakistan with workload-matched configuration, data-center delivery and expert deployment support for research, enterprise and HPC teams.

ISO 9001 & ISO 27001 certified Company
Original products with manufacturer (OEM) warranty
Nationwide delivery across Pakistan
Installation & after-sales technical support

Configurable to your workload

Pick alternative CPU, memory, storage or warranty and submit — we will price your exact build within one business day. The base configuration is captured under Detailed Specification.

Build to order

AI Accelerator (NPU, 8× per node)

The Atlas 800 9000 carries eight Ascend 910B NPUs on an HCCS-interconnected baseboard. Availability and export status vary by region — we confirm allocation and compliance before quoting.

8× Ascend 910B (single node) Base Standard 8-NPU training node with HCCS.

Multi-node cluster (e.g. 4 / 8 / 16 nodes) Scale-out training pod with RoCE fabric.

Other accelerator configuration — specify Tell us your framework (MindSpore / PyTorch-Ascend), model size and node count, and we will scope the NPU configuration and cluster fabric.

Host Processor (Kunpeng 920, ARM64)

Quad Kunpeng 920 host CPUs handle data loading and orchestration for the 8 NPUs. Higher core counts help data pipelines. ARM64 software only.

4× Kunpeng 920 · 48-core Base Balanced host for data pipelines (base).

4× Kunpeng 920 · 64-core Wider data-loading throughput.

Other Kunpeng configuration — specify Kunpeng 920 host SKUs supported by the Atlas 800 9000. We confirm configuration before quoting.

Host Memory

Large host RAM keeps the 8-NPU complex fed and supports data staging. 2 TB is a balanced default for large-model training.

1 TB host DDR4 Entry — fine-tuning / smaller models.

2 TB host DDR4 Base Balanced large-model training default.

3 TB host DDR4 Heavy data staging / large datasets.

Other memory configuration — specify Tell us model size and dataset staging needs and we will size host memory.

Local Storage

Fast local NVMe for datasets and checkpoints; clusters also attach a parallel/shared filesystem (e.g. OceanStor). Pick capacity by dataset size.

2× 1.92 TB NVMe (RAID-1) — boot/base Base OS/boot; datasets on shared FS.

4× 3.84 TB NVMe (scratch) ~15 TB fast local scratch.

8× 7.68 TB NVMe (scratch) ~61 TB local for large datasets/checkpoints.

Other storage configuration — specify Describe dataset size, checkpoint cadence and whether a shared/parallel filesystem is used.

Scale-out Fabric

Single-node training needs only front-end NICs. Multi-node training pods use one 200 Gb RoCE port per NPU for non-blocking all-reduce.

Front-end only: 2× 100 GbE (single-node) Base

4× 200 Gb RoCE

8× 200 Gb RoCE (one per NPU)

Power

An 8-NPU node draws ~5–6 kW — 240 Vac and high-current rack PDUs are required. PSU count is fixed by configuration.

4× 3000 W PSU (redundant, 240 Vac) Base

Warranty / Support

AI infrastructure is typically tier-0 — mission-critical support minimizes training downtime.

3-year onsite (base) Base

24×7 4-hour onsite · 3/5 years Recommended for training clusters.

Mission-critical SLA · 5 years Production training pods.

Software Stack (ARM64)

ARM64 host OS with the Ascend AI stack. We can pre-validate CANN / MindSpore / PyTorch-Ascend and cluster orchestration.

openEuler + CANN + MindSpore Base

openEuler + CANN + PyTorch (Ascend adapter)

Kylin (ARM64) + Ascend stack

No OS — bare metal

Quantity

Additional notes

Full name *

Company

Work email *

Phone *

Confidential. Response within one business day.

Huawei Atlas 800 Training Server (Model 9000) — Technical Use Cases

AI / ML & LLM Training

Multi-GPU/accelerator training and fine-tuning of deep-learning and large-language models.

High-Throughput Inference

Low-latency, high-concurrency inference serving for production AI applications.

HPC & Research

GPU/NPU compute clusters with high-speed InfiniBand/RoCE fabric for scientific and engineering workloads.

Data Science & Analytics

Accelerated analytics, model development and in-memory data pipelines for enterprise data teams.

Why Buy Huawei Atlas 800 Training Server (Model 9000) from Toprated

Genuine Products

Original hardware with manufacturer (OEM) warranty — not grey-market imports.

Ready Stock

In-stock items dispatch within 24–48 hours from Lahore; build-to-order on the shortest lead time.

Competitive B2B Pricing

Itemised, procurement-ready quotations with GST and optional services listed separately.

Warranty & Support

Manufacturer warranty plus extended/onsite support options aligned to your SLA.

Nationwide Delivery

Fast delivery to Lahore, Karachi, Islamabad, Rawalpindi, Faisalabad and across Pakistan.

Expert Deployment

Pre-sales sizing, installation, configuration and after-sales technical support.

Certified & Accountable

ISO 9001 & ISO 27001 certified processes; PSEB-registered supplier.

Confidential Handling

Every business and institutional inquiry handled discreetly and professionally.

The Huawei Atlas 800 Training Server (Model 9000) is supplied for business, corporate, data-center and institutional use only. It is enterprise-class equipment intended for production IT environments and typically requires a rack/server-room environment, redundant power and professional deployment. It is not a home, personal, gaming or student-use product. For business, government and institutional procurement — contact us with your organisation's requirement.

Also known as

Atlas 800 9000 Atlas 800 Training Huawei Atlas 800 Ascend 910

Huawei Atlas 800 Training Server (Model 9000) — Frequently Asked Questions

All listed Huawei Atlas 800 Training Server (Model 9000) units are brand new with manufacturer warranty unless a listing is explicitly marked as Refurbished or Used.

Pricing depends on your final configuration and quantity. Share your requirement and Toprated returns an itemised quotation, with GST shown separately, within one business day.

Yes — common configurations are held in ready stock, and custom builds are sourced on confirmed order with the shortest available lead time.

In-stock items ship within 24–48 hours from Lahore. Deliveries to Karachi, Islamabad, Faisalabad and Rawalpindi typically reach in 2–4 working days.

Quotations are itemised — hardware, GST and optional installation/configuration services are listed separately so you select only what you need.

Every unit carries manufacturer warranty, with extended and on-site/next-business-day support options available. Toprated also provides local installation and after-sales technical support.

Yes. Toprated supplies corporate, enterprise, data-center, government, education and institutional buyers, with documentation suited to formal procurement, backed by ISO 9001 / ISO 27001 certified processes.

We configure the Huawei Atlas 800 Training Server (Model 9000) with the supported NVIDIA, AMD or Intel accelerators and high-speed InfiniBand/RoCE fabric for your AI/ML training or inference workload. Share your model size and we recommend the optimal build.

Yes — our team helps right-size GPU count, memory, NVMe storage and network fabric to your model and dataset, and supports cluster deployment.

Yes — GPU drivers, CUDA/CANN/ROCm stacks, containers and the OS or hypervisor can be installed and validated before delivery.

Form Factor	4U Rack
Accelerators	8× Huawei Ascend 910B AI processors (NPU), fully interconnected via HCCS
NPU interconnect	HCCS mesh — high-bandwidth all-to-all between the 8 NPUs
Host CPU	4× Huawei Kunpeng 920 (ARM64)
Architecture	ARM64 host + Da Vinci NPU — AArch64 software only
Memory profile	DDR4 RDIMM (host) — multi-channel per Kunpeng socket
Memory (base)	2 TB host DDR4 (sized for 8-NPU feeding) — configurable
Storage	Local NVMe/SAS hot-plug + M.2 boot; pairs with parallel filesystem in clusters
Scale-out fabric	Up to 8× 200 Gb RoCE (one per NPU) for multi-node training
Front-end network	On-board GbE + 25/100 GbE management/data
Cooling	High-performance air cooling (liquid-cooled variants exist)
Power Supply	4× 3000 W PSU (redundant) — 240 Vac, high-current PDU required (~5.6 kW node)
Management	Huawei iBMC (Redfish/IPMI)
Software stack	CANN toolkit · MindSpore · PyTorch (Ascend adapter) · openEuler/Kylin host OS
Warranty (base)	3-year onsite — mission-critical SLA recommended for training clusters

Huawei Atlas 800 Training Server (Model 9000)