G1395-3000WNA – 3000W CRPS Power Supply for POE, Networking, Telecom, and AI Applications

The G1395-3000WNA is a robust CRPS power supply engineered for POE switches, networking, telecommunications, and AI applications. Its compact 1U CRPS-standard form factor (185 x 73.5 x 40 mm) offers excellent space efficiency for high-density systems. This unit delivers a main output of 54.5V at 55A, complemented by a 12V standby output rated at 3A. It supports a wide input voltage range of 90–264Vac / 180–300Vdc, ensuring compatibility with global power sources. Equipped with full digital control and PMBus 1.2 interface, the power supply provides intelligent power monitoring and remote management capabilities. Platinum-level efficiency combined with active power factor correction (PFC) ensures reliable and energy-efficient operation. Smart fan control optimizes thermal management while minimizing noise, and the reverse airflow option provides flexible system integration to suit various configurations. Certified to meet UL, CE, FCC, CB, and additional global safety and EMC standards, the G1395-3000WNA delivers dependable performance for demanding enterprise environments.

Features

CRPS-185: 185×73.5x40mm(LxWxH)

CRPS-265: 265×73.5x40mm(LxWxH)

3A Max standby output current

Voltage Tolerance : 54.5Vdc ±3%(52.8-56.1Vdc)

Hot-plug

Full Digital control

Active Power Factor Correction

Intelligent-thermal Fan Control

N+1 Redundant

Reverse Airflow Option

Applications

POE Switch

Networking

Telecom

Artificial Intelligence

Router System

Data Centers

5G Base Stations

IoT Gateways

Approvals

UL/CUL

CB

TUV/Mark

CCC/CQC

FCC

CE

Specifications

Output Power (W): 3000
Length (mm): 185
Width (mm): 73.5
Height (mm): 40
Mounting Type: Hot pluggable
Minimum Output Current (A): 0
Maximum Output Current (A): 55
Output Voltage (V): 54.5
Minimum Output Power (W): 0
Maximum Output Power (W): 3000
Minimum Input Voltage (V): 90
Maximum Input Voltage (V): 264

 

Model Selection Comparison Table

Model

Power Class Role Input Form Factor Recommended Use
G1395-3000WNA High-Density Compute + storage blend AC/DC CRPS-185

Hybrid clusters and analytics

G1395-3500WNA

Extreme GPU inference and POP compute AC/DC CRPS-185

Large AI and data bursts

Deployment Scenarios

The G1395-3000WNA delivers 3000W continuous output engineered for GPU-capable compute pools, NVMe-dense storage backplanes, high-throughput virtualized clusters, massive surveillance grids, and AI container nodes experiencing sustained heavy power draw. This power tier helps organizations standardize on a single supply footprint across compute and storage layers, reducing maintenance complexity while supporting future scale without immediate PSU replacement. It fits environments where data ingestion, model execution, database indexing, and multi-tenant traffic processing frequently overlap in real time.

 

Scenario

Expected Load Pattern Why 3000W Tier Fits
AI inference racks Continuous compute flow

Maintains rail stability at sustained GPU demand

NVMe archive/storage

High write flush cycles Headroom protects against rebuild power spikes
Hybrid virtualization CPU+IO concurrency

Allocates sufficient peak margin for combined tasks

Surveillance clusters

24/7 ingest + analytics Handles motion events without power sag
Elastic cloud edge Auto-scaling workloads

Reserves growth capacity for microservices

Multi-node POP compute

Router+cache+storage

Reduces brownout risk under failure rollover

Power Architecture & Reliability Design

The G1395-3000WNA utilizes a high-current AC/DC conversion stage optimized for racks that require fast transient absorption and stable voltage rails under multi-domain workloads. It is engineered for data center environments running virtual machines, indexing nodes, distributed cache services, and containerized inference layers concurrently, where load overlap and rapid power transitions are routine rather than exceptional.

 

Electrical routing is reinforced to tolerate continuous high-temperature operation, while airflow channels are shaped to maintain predictable thermal behavior in deep-rack configurations. This design remains stable even as dust accumulation increases static pressure, avoiding the throttling or regulation drift often observed in less robust power supplies deployed over long service intervals.

 

The power stage is tuned to deliver consistent parallel behavior in redundant N+1 configurations, allowing infrastructure teams to perform rolling upgrades or maintenance without risking load imbalance or collapse. PMBus telemetry provides visibility into operational trends such as temperature rise, load distribution, and regulation stability, enabling proactive intervention before critical thresholds are reached. As a result, the G1395-3000WNA is well suited for high-density data halls that prioritize uptime, scalability, and predictable long-term power behavior

Power Operating Notes

Reference Condition

Suggested Guidance
GPU inference workload

Leave margin for transient events

Large storage fabrics

Monitor temp under constant flush duty
Virtualization clusters

Maintain balanced fan intake zones

Surveillance analytics

Watch power swing during event spikes
Deployment indoors

Dust control extends lifespan

Multi-node racks

PMBus health polling recommended
POP metro cores

Size cabling for high continuous draw

Fleet integration

Standardize series for easier swap

FAQ

Q1. Best scenarios?
Heavy compute clusters, mixed NVMe storage + inference, surveillance analytics.

 

Q2. Suitable for 24/7 operation?
Yes, the design supports always-on server infrastructure.

 

Q3. How does 3000W compare to 3500W?
3000W is ideal when capacity is required without full extreme headroom.

 

Q4. Burst protection?
Stable under combined CPU+GPU power peaks.

 

Q5. How well does it run multi-tenant workloads?
High concurrency environments are exactly its intended class.

 

Q6. Rack thermal constraints?
Airflow shaping helps maintain thermal reliability when packed tightly.

 

Q7. Appropriate for deep RAID write flushes?
Yes, sustained current output prevents regeneration instability.

 

Q8. When to choose this model?
When planning for balanced high-density compute with future scalability.

 

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