Edge AI Box · Intel Core i9-13900 · RTX MXM GPU

AE-760EBT: Intel® Core™ i9 + NVIDIA® RTX MXM Industrial Edge AI PC

13th Gen Intel® Core™ i9-13900 (24C/32T) + NVIDIA RTX 4060/4070/4090/5080/5090 MXM, actively cooled by dual 80 mm industrial fans — desktop-class AI inference for machine vision, AMR and edge generative AI.

  • NVIDIA RTX MXM discrete GPU (up to RTX 5090) for CUDA / TensorRT inference
  • 4× 2.5GbE Intel i226-IT, 2× CAN FD, 8 DI / 8 DO isolated for vision & automation
  • 9–36V wide voltage + remote power, dual 80 mm PWM fans, -20°C to +60°C 24/7 operation

AE-760EBT RTX MXM Industrial PC

AE-760EBT  MXM Industrial AI BOX PC Overview

i9-13900 + RTX MXM, Engineered with Industrial Active Cooling

The AE-760EBT bridges the long-standing gap between consumer-grade GPU workstations and rugged industrial controllers. It combines the 13th Gen Intel® Core™ i9-13900 processor (24C/32T, 8 Performance-cores + 16 Efficient-cores, up to 5.6GHz, 65W base / 219W turbo power) with NVIDIA RTX MXM 3.1 modules ranging from RTX 4060 to RTX 5090 on a single industrial-grade motherboard.

To sustain full P-core turbo performance of the i9 processor together with continuous MXM GPU workloads under intensive AI computing, the chassis is equipped with dual 80mm industrial-grade ball-bearing PWM fans dedicated to a copper heat-pipe thermal array. The cooling system is engineered specifically for 24/7 continuous operation, featuring fan-failure monitoring and tachometer feedback, rather than conventional consumer-grade cooling solutions.

For machine vision builders, the four 2.5GbE i226-IT ports aggregate multiple GigE Vision cameras directly into a single inference node. For AMR / AGV and vehicle integrators, 9–36V wide-voltage input, dual CAN FD, isolated DIO and a remote power terminal allow drop-in integration with existing wiring harnesses. For outdoor and roadside edge deployments, the -20°C to +60°C operating range, IEC 61000-4 immunity and replaceable industrial fans enable serviceable, high- throughput deployment in ventilated enclosures.

The AE-760EBT is a single platform that replaces three traditional building blocks: an industrial PC, a GPU workstation, and an external I/O / network gateway.

AE-760EBT Key Engineering Highlights


Scalable AI Inference: NVIDIA® RTX™ MXM Discrete GPU Architecture

RTX 4060 / 4070 / 4090 / 5080 / 5090 MXM modules — up to 80+ TFLOPS for CUDA, TensorRT and Tensor Core AI inference.


Desktop-Class Processing: 13th Gen Intel® Core™ i9-13900 (24C/32T)

24C/32T (8 P + 16 E), up to 5.6 GHz, 36 MB L3, DDR5 up to 64 GB, TPM 2.0 — desktop-class CPU for AI pre/post-processing.


High-Throughput Vision Networking: Quad 2.5GbE Intel® i226-IT Ports

Quad Intel i226-IT controllers for Muti-camera aggregation, network segmentation and PTP-grade determinism.


Field-Bus Mastery: Native Dual CAN FD & Isolated Digital I/O

2× CAN FD, 4× isolated RS232/485, 8 DI / 8 DO opto-isolated (3.3V/5V/12V) for direct field-bus integration.


Rugged Industrial Chassis

Extruded aluminum frame with copper heat-pipe arrays from CPU and MXM GPU to a finned heat exchanger — built for serviceability.


9–36V + Remote Power

DC jack + 4-pin Phoenix + 2-pin remote power on/off — direct fit for 12V/24V vehicle and cabinet wiring.


Active Thermal Engineering: Dual 80mm Industrial PWM Fans

2× 80 mm (8 cm) ball-bearing PWM fans, >70,000 hrs MTBF, fan-fault & tachometer monitoring — sustains full i9 + RTX load.

AE-760EBT Technical Specifications (Key Components & Interfaces)

ProcessorIntel® Core™ i9-13900 (24C/32T: 8 P-cores + 16 E-cores, up to 5.6 GHz, 36MB L3, 65W base / 219W turbo)
Integrated GPUIntel® Iris® Xe / UHD Graphics
Discrete GPU (MXM)NVIDIA RTX 4060 / 4070 / 4090 / 5080 / 5090 MXM (optional)
CoolingActive cooling – 2× 80 mm (8 cm) industrial ball-bearing PWM fans, >70,000 hrs MTBF, fan-fault & tachometer monitoring
Memory2× DDR4 SO-DIMM, up to 64 GB
Storage1× 2.5″ SATA SSD/HDD + 1× mSATA + 1 x PCIe
Display2× HDMI 2.0 Type-A, up to 4096 × 2160 @ 30 Hz
Ethernet4× Intel i226-IT 2.5GbE LAN
Serial4× RS232/485 (Isolated)
CAN Bus2× CAN FD
Digital I/O8× DI + 8× DO, opto-isolated (3.3V / 5V / 12V)
USB4× USB 3.2 Gen1 Type-A (5 Gbps)
Wireless / WWAN1× M.2 B-Key (4G/5G + SIM), 1× M.2 E-Key (Wi-Fi/BT)
SecurityTPM 2.0
Power InputDC 9–36V (jack 5.5×2.5 mm + 3-pin Phoenix), Remote Power On/Off
Operating Temp.-20°C to +60°C (PassMark BurnInTest at full i9 + RTX load, no thermal throttling)
Shock / Vibration15G @ 11ms / 5–500 Hz, 1 Grms
Dimensions / WeightCompact active-cooled chassis with dual 80 mm fan exhaust / approx. 6.0 kg
MountingWall / Side / DIN-rail / VESA
OS SupportWindows 11 Pro, Ubuntu, Linux

This overview supports early-stage system verification. For full electrical, mechanical, EMI/EMS and environmental specifications, please refer to the datasheet.

i9-13900 + RTX 4060 MXM — Heavy-Load Inference Compute & Power-Efficiency

Measured engineering reference for the AE-760EBT default SKU (Intel® Core™ i9-13900 + NVIDIA® RTX 4060 MXM, 8 GB GDDR6). Values reflect sustained heavy-load inference (CUDA + Tensor Core, batch ≥8) inside the industrial-grade chassis with dual 80 mm PWM cooling at 25 °C ambient. Use these as a planning baseline; final numbers depend on model, batch size and thermal envelope.

Metrici9-13900 (CPU)RTX 4060 MXM (GPU)System (CPU + GPU)
Peak compute~0.9 TFLOPS FP32 (AVX2/AVX-512 disabled, 24C/32T)15.1 TFLOPS FP32 / 121 TFLOPS FP16 Tensor / 242 TOPS INT8≈ 242 TOPS INT8 effective for vision inference
Sustained heavy-load power125–180 W (PL1 125 W, PL2 219 W, sustained ~150 W typical)95–115 W (MXM TGP capped at 115 W in chassis)260–320 W under joint CPU+GPU inference load
Idle / light-load power18–25 W package8–12 W (P8 idle)35–55 W full system idle
Inference power-efficiency~6 GFLOPS/W (FP32, AVX2)≈ 2.1 TOPS/W INT8 sustained≈ 0.85 TOPS/W INT8 measured at the wall
YOLOv8-s @ 640×640 (TensorRT INT8)~38 FPS (OpenVINO, single stream)~410 FPS (batch=8, INT8)≈ 1.4 FPS / W (camera-stream throughput)
ResNet-50 inference (ImageNet, INT8)~310 img/s~3,950 img/s (batch=32, TensorRT)≈ 13.5 img/s / W
LLaMA-2 7B (INT4, llama.cpp / TensorRT-LLM)~6 tokens/s (CPU only, Q4_K_M)~58 tokens/s (8 GB VRAM, batch=1)≈ 0.20 tokens/s / W end-to-end
Stable Diffusion 1.5 (512×512, 20 steps)Not practical (>40 s/image)~2.4 s/image (FP16, TensorRT)≈ 1 image per 720 J of wall-plug energy
Thermal headroom (dual 8 cm PWM, 25 °C amb.)Tj ≤ 92 °C @ 180 W sustainedTj ≤ 78 °C @ 115 W sustainedNo thermal throttling observed up to 320 W system load
Acoustic level @ 1 m (full inference load)≈ 48 dB(A) — both 80 mm fans at ~70% PWM
Best perf / W
≈ 2.1 TOPS / W
RTX 4060 MXM, INT8 sustained inference at 110 W TGP.
Typical heavy-load draw
260 – 320 W
Joint CPU+GPU inference; size 9–36 V DC supply for ≥ 400 W margin.
Vision throughput
~410 FPS YOLOv8-s
INT8, batch=8, 640×640 — supports 8+ concurrent 2.5GbE camera streams.

Figures derived from Bitech engineering bench data (TensorRT 9.x, CUDA 12.x, Ubuntu 22.04, kernel 6.5) on the AE-760EBT reference unit. Customer workloads, model precision and

ambient temperature will shift absolute numbers — contact our engineering team for an application-specific power & thermal budget review.

  AE-760EBT Target B2B Application Scenarios

Multi-Camera Machine Vision & Automated Optical Inspection (AOI)

GigE Vision aggregation across 4× 2.5GbE LAN with RTX-accelerated YOLO / defect-detection inference for SMT, semiconductor and packaging lines.

Onboard AI Controller for AMR / AGV & Autonomous Vehicles

9–36V vehicle power, CAN FD motion bus and 3D point-cloud / SLAM acceleration with i9-13900 + RTX MXM on a single rugged active-cooled unit.

Edge Generative AI & Infrastructure Operations

Run Stable Diffusion, LLaMA-class and ONNX models locally with TensorRT on RTX 4090 / 5090 MXM — no cloud dependency.

Roadside & Outdoor V2X / ITS

Wide-temperature, wide-voltage, IEC 61000-4 immunity for traffic vision, ANPR and intersection edge AI.

Digital Twin & 3D Visualization HMI

Dual 4K HDMI outputs driven by discrete RTX GPU for CAD, BIM and operator-facing twins on the plant floor.

Robotics & Service Robot Compute

Compact actively-cooled chassis, isolated DIO and CAN FD for humanoid, inspection and service robot platforms requiring i9-class compute.

Technical Evaluation: AE-760EBT (x86) vs. AE-NJ60BT (ARM Jetson)

Both are active-cooled edge AI platforms, but they target different compute classes and software ecosystems. Use the AE-760EBT when you need x86 + CUDA-class discrete GPU; choose the AE-NJ60BT when you need an ARM Jetson Orin SoC with native GMSL2 camera ingress at lower power.

Engineering FactorAE-760EBTAE-NJ60BT
Architecturex86 — Intel Core i9-13900 (24C/32T)ARM — NVIDIA Jetson Orin Nano / NX / NX Super SoM
AI ComputeNVIDIA RTX 4060–5090 MXM, up to 80+ TFLOPS / Tensor & RT coresUp to 157 TOPS (Orin NX Super 16GB), integrated GPU + DLA
Software StackWindows 11 Pro / Ubuntu, CUDA, TensorRT, OpenVINO, ONNXNVIDIA JetPack, CUDA, TensorRT, DeepStream
Camera Ingress4× 2.5GbE GigE Vision + USB 3.24-lane MIPI CSI or 4× GMSL2 (long-distance, EMI-resistant)
CoolingActive — dual 80 mm industrial PWM fansActive — 1× smart PWM fan (low-noise, temperature-controlled)
Operating Temp.-20°C to +60°C-40°C to +70°C (wide-temp, single-fan assisted)
Power InputDC 9–36V, remote on/offDC 9–36V, remote on/off
Best ForHeavy multi-stream vision AI, generative AI on the edge, CUDA workstations in the fieldCompact multi-camera AMR/AGV perception, autonomous machines, in-cabinet vision AI
Running a large language model at the edge is bound by two things: how much memory holds the model, and how fast the accelerator generates tokens. That splits neatly into three tiers of BITECH hardware.

(Figures are 4-bit (Q4/INT4) single-stream generation; actual throughput varies with quantization, context length and runtime. Sources: NVIDIA JetPack 6.2 LLM benchmarks and independent edge-LLM inference testing.)

PlatformRuns well (4-bit)Practical ceiling7–8B speed (Q4)Memory for the modelBITECH box
x86 + RTX MXM GPU7B–34B70B quantized~100+ tok/s16–32 GB discrete VRAMAE-760EBT
Jetson Orin (CUDA GPU)2B–8B13B (AGX 64 GB)~15–40 tok/sup to 64 GB unified LPDDRAE-NJ60BT
RK3588 (6 TOPS NPU)1B–4B~7B (slow)~3–15 tok/sup to 32 GB shared LPDDRAE-3588BT

Designed for 24/7 Industrial & Vehicle Deployment

  • Operating temperature: -20°C to +60°C with full i9-13900 turbo + RTX load (storage -20°C to +60°C)
  • Active cooling: 2× 80 mm (8 cm) ball-bearing PWM fans, >70,000 hrs MTBF, fan-fault & tach monitoring, field-replaceable
  • Shock 15G @ 11ms half-sine; vibration 5–500 Hz, 1 Grms
  • EN/IEC 61000-4-2/3/4/5/6/8/11 immunity, CISPR 32 / EN 55032 Class A
  • 100% 18-hour PassMark BurnInTest under full CPU + GPU load
  • 10 year lifecycle, 24-month warranty, PCN/EOL management
  • Platform availability

    The x86 mainboard, chassis and I/O are built on the Intel Embedded Roadmap with a BOM freeze policy and 10-year availability.

    MXM GPU modules follow NVIDIA’s own generational cycle, which is shorter. We track module availability and issue PCN with a last-time-buy window when a module reaches EOL — and because the MXM 3.1 Type-B slot is a standard interface, a successor module can be qualified into the same chassis without redesigning your enclosure.

Specifications are based on factory validation. Final environmental performance should be confirmed against the customer’s installation profile.

Technical FAQ

What is the maximum sustained MXM GPU power the chassis supports?

The mainboard hard-caps the MXM 3.1 Type-B slot at 115 W Total Graphics Power.

This is a deliberate design decision, not a limitation we discovered late. A compact industrial chassis cannot dissipate 175 W of GPU heat continuously while also sustaining i9 turbo. Capping in the mainboard means performance is deterministic and repeatable instead of throttling unpredictably under sustained load.

What this means per module:

  • RTX 4060 MXM (115 W) — runs unthrottled at full factory clocks. This is the reference SKU behind all published benchmarks.
  • RTX 4070 / 4090 / 5080 / 5090 MXM — can be fitted, but operate at the 115 W tier. You gain VRAM capacity and Tensor Core count, not raw clock headroom.

If your workload requires sustained 175 W GPU power, this chassis is not the right fit — and we will say so at RFQ rather than after delivery.

How does the AE-760EBT handle Core i9-13900 power limits and thermal throttling under full AI inference load?

The BIOS applies power profiles tailored for industrial deployment: PL1 (long-term) locked at 125 W, PL2 (short-term) up to 219 W for 28 seconds.

To sustain this, the system uses 4× composite copper heat pipes mated directly to the CPU die, drawing heat to an aluminium fin array cooled by twin 80 mm high-static-pressure PWM fans.

In a 55°C ambient environment running continuous validation workloads, CPU core temperature stabilises below 92°C, allowing P-cores to hold a steady 3.0–3.5 GHz baseline indefinitely. No thermal throttling was observed up to 320 W combined system load.

Are the four 2.5GbE ports independent or bridged? Will they contend for bandwidth at full line rate?

Completely independent. There is no single-channel switch chip bridging traffic.

The mainboard integrates 4× independent Intel i226-IT 2.5GbE controllers, each on a dedicated PCIe lane.

Aggregating four GigE Vision cameras at full 2.5 Gbps line speed puts total system throughput near 10 Gbps. This native architecture prevents internal bus congestion, packet collision and dropped frames at the edge — the failure mode that makes bridged four-port designs unusable for multi-camera inspection.

What are the chassis dimensions, and what clearance does the cooling design need?

Chassis dimensions are 240 × 200 × 60 mm] at approximately 6.0 kg, with dual 80 mm fan exhaust on one face.

Airflow clearance: allow at least 10 mm of unobstructed space in front of the fan exhaust and intake faces. Mounting the unit flush against a cabinet wall on the exhaust side will recirculate hot air and reduce the sustained power envelope.

Mounting options: wall, side, DIN-rail and VESA. The fan brackets sit outside the sealed internal chassis, so field replacement does not require opening the thermal assembly.

What storage does the AE-760EBT use, and how does that affect large model loading?

Storage configuration: 1× M.2 2280 PCIe NVMe + 1× 2.5″ SATA SSD/HDD + 1× mSATA.

Why this matters for edge LLM workloads: a 34 B model quantised to Q4 occupies roughly 20 GB on disk. Load time differs substantially by interface — SATA at ~550 MB/s takes well over 30 seconds, while PCIe NVMe loads the same model in a few seconds.

For deployments that load models on boot or swap between models at runtime, specify the NVMe configuration at RFQ. For deployments that load once and keep the model resident in VRAM, SATA is sufficient.

Our vehicle bus drops voltage during motor acceleration. What protects the DC input stage?

The AE-760EBT accepts a wide-range DC 9–36 V input with reverse-polarity protection, over-current cutoff, and transient voltage suppression (TVS) diodes on the input stage.

For the typical case — a 12 V or 24 V battery bus sagging toward 9 V for up to 100 ms during high-torque motor startup — the onboard DC-DC converters and solid-state capacitor bank hold internal rails stable, preventing resets or unplanned shutdowns.

Input is available on a 5.5×2.5 mm DC jack, a 3-pin Phoenix terminal, and a 2-pin remote power on/off terminal, so it drops into existing vehicle and cabinet wiring without an adapter harness.

Are the dual CAN FD ports isolated, and how is bus termination handled?

Yes — both CAN FD ports carry 4000 V isolation withstand to break ground loops and block high-voltage spikes from switching contactors and heavy industrial equipment. The four RS-232/485 ports and the 8 DI / 8 DO block are opto-isolated as well.

For impedance matching on long field-bus runs, the mainboard provides onboard 120Ω termination resistors on jumper pins. Two terminators at the two ends of the bus read approximately 60Ω across the pair — the standard check. This removes the need for external termination dongles and eliminates reflection-induced data loss.

What cabinet conditions does the active cooling require?

Because the AE-760EBT uses dual 80 mm exhaust fans rather than passive conduction, the enclosure must move air. Requirements:

  • Filtered air intake paths or louvers in the cabinet — a fully sealed, unventilated enclosure will not work with this platform
  • Operating range −20°C to +60°C at the intake, storage −40°C to +80°C
  • Clearance in front of both the intake and exhaust faces so hot air is not recirculated

For sealed, dust-prone or fully passive enclosures, an ARM-based platform without a discrete GPU is the better architectural fit — the trade-off being that you lose the full CUDA and Windows software stack.

Is the TPM 2.0 hardware-based, and do you support factory secure-boot key flashing?

It is a discrete hardware security chip on the Infineon SLB9670 platform, not CPU-simulated firmware TPM (fTPM), which avoids the class of vulnerabilities associated with fTPM implementations.

For grid, critical infrastructure and high-security industrial deployments, BITECH supports factory-level UEFI Secure Boot customisation. Your PK, KEK and db keys can be flashed into custom BIOS firmware during production, locking the boot state against physical firmware injection.

What is the platform lifecycle, given that MXM GPU modules turn over faster than embedded CPUs?

Two different clocks, and it is worth being precise about which is which.

The x86 mainboard, chassis and I/O are built on the Intel Embedded Roadmap under a BOM freeze policy once an OEM configuration is approved, with 10-year availability and formal PCN issued 6 to 12 months ahead of any unavoidable component change.

MXM GPU modules follow NVIDIA's own generational cycle, which is shorter. We track module availability and issue PCN with a last-time-buy window when a module reaches EOL. Because MXM 3.1 Type-B is a standard interface, a successor module can be qualified into the same chassis without redesigning your enclosure or re-certifying the mechanical envelope.

Warranty is 24 months on the complete unit. Every unit passes 18-hour PassMark BurnInTest under full CPU and GPU load before shipment.

Related

Compare, apply, and spec the AE-760EBT

The AE-760EBT is the x86 + RTX MXM platform in the BITECH edge-AI range — for GPU-heavy local LLM and vision work that needs discrete VRAM in a compact, thermally-validated enclosure. Compare it with the other edge-AI platforms, see where it fits, and size it against a real workload.

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