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Machine indexAetina / MegaEdge AIP-FR68

Aetina MegaEdge AIP-FR68

Qualcomm Cloud AI 100 Ultra · up to 2 cards

A complete OEM workstation for on-premises inference, using Qualcomm Cloud AI accelerators and the AI Inference Suite.

Up to 2 accelerator cardsReference memory
x86 host + acceleratorQualcomm AI ecosystem

BEFORE IT ARRIVES

Power, cooling & your space.

What this configuration needs on your premises.

Requirements reviewed 2026-09-29
Lab assessment · based on the evidence below

Integration required

An industrial DC-powered system that needs a complete integration quote. The bare system does not include its power supply or accelerator cards.

Power rating

Published detail

Up to 600 W full-load supplier rating for the chassis family. Optional Cloud AI 100 Ultra cards are rated 150 W each. No measured AC wall result for the selected bundle. [1]

Electrical input

Published detail

24–48 V DC through a 4-pin terminal block; up to 600 W DC input. The AIP-FR68-A2 bare system excludes the power supply. [1]

Outlet & circuit

Not verified

No machine-specific branch-circuit requirement verified. Check the nameplate, regional cord and other loads on the same circuit.

Machine cooling

Published detail

Chassis thermal design supports two passive Cloud AI 100 Ultra cards. Passive cards rely on system cooling; they do not make the complete computer fanless. [1]

Operating limits

Published detail

Chassis ratings: 0–50°C with a 165 W passive GPU; 0–40°C with a 300 W active GPU. Obtain approval for the exact one- or two-card Qualcomm bundle. [1]

Noise in the workspace

Not verified

No comparable noise measurement under an AI workload verified. Ask for dB(A), distance, workload and ambient conditions; audition it before placing it beside people.

ACTUAL CONSUMPTION

Power at the wall

PSU capacity, chip TDP and measured consumption describe different things. Only measurements with a stated configuration and test method appear here.

Idle and AI-load wall power: not verified.

No attributable wall-power test for this configuration was established in this review. Measure at the outlet with the exact model, workload, runtime and power mode recorded.

Share a power measurement

Room cooling

Allow for sustained room heat, including after office hours. A ventilated equipment room may be more practical for multiple systems or continuous jobs. An internal liquid cooler does not remove the need for room cooling.

Lab planning guidance. Office suitability depends on the installed configuration, shared circuits, heat removal and acceptable noise; a workstation label alone does not settle it.

Space & installation

Enclosure
340 × 215 × 279 mm
Weight
11 kg · confirm card population
  • Have the integrator specify the AC/DC supply, wiring and circuit. The DC terminal is not a mains connection.
  • Keep air inlets and exhausts unobstructed, with room for cables and servicing. An enclosed cupboard needs its own ventilation; the enclosure dimensions are not an airflow clearance.
  • Confirm the final card count, thermal configuration and mounting hardware before installing.
Estimate electricity use & room heat

Enter average power at the wall for the hours you are modeling, or an explicit planning assumption. Supply wattage and chip TDP are not consumption measurements.

Add wall power to calculate a scenario.

Scenario only. Hours outside this period are excluded: include idle time for an always-on system. Displays, networking, UPS losses and room air conditioning are extra. Heat assumes the computer and power supply release their heat into this room; it does not size a circuit or an HVAC system. Currency selects your tariff’s unit, with no conversion.

Sources & review scope (1)

Manufacturer documentation and attributed first-hand hardware inspections, scoped to the named model or configuration. “Not verified” identifies a gap in this review, not a claim that the manufacturer has no documentation. Installation assessments are the Lab’s interpretation.

  1. Aetina · AIP-FR68 datasheet and accelerator options
Opening model configurations…
01 / PRIVACY

Your data has a home.

Keep sensitive processing on your infrastructure. Inspect every connection in the complete stack.

02 / SECURITY

You set the boundaries.

Control access, connectivity and updates. A local machine still needs a secure deployment.

03 / TOKEN ECONOMICS

Own the capacity.

Generate tokens on your own compute. Understand the full cost of the useful work it delivers.

DEPLOYMENT NOTEBOOK / Qualcomm Cloud AI

Compilation is part of the configuration

01

Target the actual accelerator

QEfficient converts supported model checkpoints for Qualcomm Cloud AI accelerators. A supported model name is not evidence that an artifact has been compiled for your card population.

02

Save the compiled configuration

Keep SDK and compiler versions, precision, batch and context settings with the model revision. Match those settings when reproducing results.

03

Evaluate the complete appliance

Confirm host resources, accelerator memory, networking and service support with the system supplier. Measure application quality and latency on that complete system.

Lab synthesis of supplier guidance and deployment questions · reviewed 2026-09-13. Reference-platform details may differ from this machine.

Qualcomm QEfficient project

SHARED WORK AROUND THIS PLATFORM

Setups you can build on.

Reference-platform guidance and field records. Exact OEM configurations need their own validation.

All setups
Qualcomm

THE PLATFORM BEHIND THE MACHINE

Cloud AI 100 Ultra

1 catalog configuration

Shared silicon does not guarantee identical performance. Compare the memory, cooling and configuration of each machine.
Explore this platform

BEYOND THE SPECIFICATION

Lessons for running this machine.

Published guidance and checklists to help you investigate the full deployment.

Share your experience

THE CONFIGURATION

Inside the machine

Configuration
AIP-FR68 / up to 2 Cloud AI 100 Ultra cards; exact build on request
CPU / accelerator
Qualcomm Cloud AI 100 Ultra · up to 2 cards
Memory
Up to 2 accelerator cards
Memory bandwidth
See source; no lab measurement
Architecture
x86 host + accelerator
Operating system
Linux · Qualcomm AI Inference Suite for On-Prem
Storage
Confirm with manufacturer

ON YOUR PREMISES

Space, power & connectivity

Form factor
Deskside workstation
Dimensions
340 × 215 × 279 mm
Weight
11 kg · confirm card population
Power rating
Up to 600 W full-load supplier rating for the chassis family. Optional Cloud AI 100 Ultra cards are rated 150 W each. No measured AC wall result for the selected bundle.
Connectivity
See manufacturer configuration
Availability
Supplier inquiry · confirm regional availability

Power supply ratings and processor TDP are not measured wall consumption. Supplier stock and regional delivery can change.

Electrical, cooling & installation details

BEFORE YOU CHOOSE

Supports up to two Cloud AI 100 Ultra cards. Confirm the accelerator population and memory with the supplier.

128 GB is the memory-screen reference for one Cloud AI 100 Ultra card; availability to a compiled model depends on the runtime.

Qualcomm model conversion and runtime support require validation. A CUDA result does not establish compatibility.

The AIP-FR68-A2 orderable bare system excludes CPU, RAM, SSD, GPU card and power supply. Obtain a complete accelerator bundle quote.

Manufacturer specifications

Help improve this record. Suggest a correction

IN THE FIELD

Deployment experiences

Operating records from customers, contributors and the Lab.

All deployments
ADD TO THE SHARED RECORD

Where does your AI run?

In an office, a factory, an engineering lab or beside your test equipment. Share a deployment and keep the people behind it credited.

Contribute a deployment

THE SHARED TECHNICAL LIBRARY

Knowledge around this machine.

Supplier recipes, community experience and UT’s deployment lessons, connected to the hardware.

Explore 3 resources
RecipesSupplier

Compile models for Qualcomm Cloud AI

QEfficient connects supported model checkpoints to Qualcomm’s accelerator toolchain.

Qualcomm Cloud AIQEfficient
For your deployment

Preserve card generation, SDK, model revision and compiler settings. A library support entry is not an Aetina performance result.

OperationsUnderstand Tech

Offline is a property of the whole stack

Examine what still connects beyond the premises.

Across workplaces
For your deployment

Distinguish initial installation, inference, application use, authentication and updates.

Deployment experienceUnderstand Tech

An execution agent beside the test equipment

Confidential Wi-Fi module test automation.

Across workplaces
For your deployment

Exact hardware and proprietary test assets are not disclosed. This is an application field record.

Related platform guidance does not establish compatibility with this exact OEM configuration.

THE LOCAL AI WATCH

Updates for this machine

All updates

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MEMBER RATINGS · SELF-DECLARED, NOT MEASURED

How members rate the MegaEdge AIP-FR68.

One rating per member, tied to a Lab profile. Stars count immediately; written verdicts are published after a quick review by the Lab team. A rating is an opinion about fit for a job, not a benchmark.

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THE PEOPLE BEHIND THE MACHINES

Experience with MegaEdge AIP-FR68?

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Questions, ideas and experience from putting AI machines to work. You do not need a finished deployment to contribute.

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