Yahboom Jetson Orin Nano Super 4GB RAM Development Board Kit
Bottom line: The Yahboom Jetson Orin Nano Super 4GB RAM Development Board Kit is a specs-and-price decision rather than a crowd-consensus one in the single-board computers category, priced around $522.49 on Amazon as of 2026-10-22 16:16 UTC. Check the specification table below against one or two close alternatives — on price and spec fit, not on star ratings.
As an Amazon Associate, SpecPicks earns from qualifying purchases. Full disclosure →
*Price sourced from Amazon.com. Last updated 2026-10-22. Price and availability subject to change.
Pros & Cons
Pros
- ✓ Backed by Yahboom's warranty and support channels
Cons
- ✗ Check the listed dimensions, connectors and platform compatibility against your setup before ordering
- ✗ Price, stock, shipping and returns are set by the retailer and may have changed since this page was last updated
Manufacturer description
About this item 【Core Parameters】AI Perf: 34/67 TOPS GPU:1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores CPU:6-core Arm Corte-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB LMemory:8GB 128-bit LPDDR5 68 GB/s Storage: external NVMe via M.2 Key M 【Empowered by Large Al Model, Enhanced Human-Computer Interaction】Jetson Orin Super leverages three AI models and incorporates an AI voice interaction module. This multimodal visual system matches the scene being described, enabling environmental awareness and AI visual gameplay. Combined with a large-scale voice module and camera, it…
SpecPicks Verdict
SpecPicks scored Yahboom Jetson Orin Nano Super 4GB RAM Development Board Kit using a rating × review-volume × price-fit model applied to published specs and reviews across the single-board computers category. Yahboom's single-board computers lineup sits within the broader category mid-tier; price and specs are the deciding factors over brand loyalty here. Judge it on the specification table and the price rather than on sentiment: check the figures that decide your use case, then put it side-by-side with two or three close alternatives in the Compare tool before clicking through.
Common buyer scenarios for single-board computers of this kind: matching it to an existing build, replacing a failing part, or upgrading from a previous-generation equivalent. Check the spec table below against your current setup — particularly socket / form-factor / power-rating fields — and confirm compatibility on the retailer's listing before purchase. Prices and stock are set by the retailer and may have moved since this page was last updated.
Key Features
- 【Core Parameters】AI Perf 34/67 TOPS GPU1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores CPU6-core Arm Corte-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB LMemory8GB 128-bit LPDDR5 68 GB/s Storage external NVMe via M.2 Key M
- 【Empowered by Large Al Model, Enhanced Human-Computer Interaction】Jetson Orin Super leverages three AI models and incorporates an AI voice interaction module. This multimodal visual system matches the scene being described, enabling environmental awareness and AI visual gameplay. Combined with a large-scale voice module and camera, it enables speech-to-text, semantic analysis, natural conversation, and real-time video analysis, enabling advanced embodied AI applications.
- 【AI Upgrade】Jetson Orin Nano series modules are compact in size but can deliver up to 34-67 TOPS of AI performance, with power consumption ranging from 7 watts to 25 watts. Compared to the Jetson Nano B01, it offers up to 80 times the performance and sets a new standard for entry-level edge AI.
- 【Highly compatible carrier board】Yahboom's carrier board is fully compatible with orin nano module. Compared to carrier boards that use Jetson Nano on the market, the newly upgraded circuit supports 25W power mode, which enables larger and more complex neural networks and fully leverages the performance of the core module. The resources, size, and interfaces of the Yahboom carrier board are consistent with the official board, with the only difference addition of power switch button.
- 【Tutorial materials provided】The JETSON system based on Ubuntu 22.04 provides a complete desktop Linux environment with accelerated graphics, supporting NVIDI-ACUDA 12.6, TensorRT 10.7.0, cuDNN 9.6.0, OpenCV 4.10.0, etc. The performance on AI LLM, VLM and visual Transformer is significantly improved compared with the previous generation.
Full Specifications
| ASIN | B0GDDT7L6Y |
|---|---|
| Brand | Yahboom |
| Manufacturer | Yahboom |
| Built-In Media | Blu-ray |
| Included Components | Blu-ray |
| RAM Memory Installed | 4 GB |
| Warranty Description | Product delivery within 90 days |
| Memory Storage Capacity | 256 GB |
| Ram Memory Installed Size | 4 GB |
| Full listing title | Yahboom Jetson Orin Nano Super 4GB RAM Development Board Kit, 34TOPS, with 48W Power Supply, Wireless Network Card, Enclosure |
Ready to buy?
Yahboom Jetson Orin Nano Super 4GB RAM Development Board Kit, 34TOPS, with 48W Power Supply, Wireless Network Card, Enclosure is listed on Amazon. Price, availability, shipping and returns are set by Amazon and its sellers — check the listing for current terms. SpecPicks earns a small commission on qualifying purchases — thank you for supporting independent review work.
*Price sourced from Amazon.com. Last updated 2026-10-22. Price and availability subject to change.
Related Single-Board Computers
Yahboom Jetson Orin Nano Super 4GB RAM… head-to-head
Side-by-side specs, prices, and a pick for each matchup — no tab-switching.
More guides & deep dives from the SpecPicks archive
Browse all articles & guides →- The Complete Voodoo5 5500 AGP Driver Guide (2026 Edition)
- RTX 4070 Super vs RX 7800 XT — Which to Buy in 2026
- How to Build a Windows 98 Retro PC in 2026
- Emulation Hardware in 2026: FPGA, Software, and Cart-Reader Ecosystems
- Best Retro Handhelds in 2026 — From $35 to $500
- Best 1440p Gaming GPUs in 2026
- Best Budget Gaming PC Build 2026 — ~$1,000 Parts List
More reviews from the SpecPicks archive
Browse all reviews →- Best SSD for the PS4 Pro in 2026: SATA Upgrade Guide
- Local LLM PC Build 2026: What 12GB of VRAM Really Runs
- Raspberry Pi Zero 2W: Privacy-Preserving Ring Alternative
- RTX 3060 12GB vs GTX 1050 Ti: What a 4GB Card Runs in 2026
- Genesis Mini and SNES Classic on a 4K Gaming Monitor: What Actually Happens to 720p
- OpenAI and Anthropic Are Giving Startups Free Compute — Here's the Local Rig That Replaces It
- Best Gaming Controller for PC and Console in 2026: 5 Picks Compared
- How to run Qwen 3 14B on NVIDIA GeForce RTX 5080
- Qwen3.6 35B-A3B on a 12GB GPU: 95 tok/s on 4070 Super, 34 on 3060
- Logitech G920 vs HORI Overdrive for Sim Racing in 2026
- Reve 2.0 Debuts at #2 for Text-to-Image: Can You Run Local Image Gen on an RTX 3060?
- Best Cooler for the Ryzen 7 5800X: Noctua NH-U12S vs ML240L
- Raspberry Pi 4 8GB vs Ryzen 5 2600 for Gemma 3 4B: Which Cheap Box Wins?
- Asus ROG Harpe II Extreme: A 24K-Gold, 65K-Sensor Gaming Mouse
- Best Budget GPU for CNN and Image-Model Training in 2026: The RTX 3060 12GB Deep Dive
- Half an MI350X in a PCIe Slot: Inside AMD’s 144GB MI350P, the First Air-Cooled CDNA 4 Card
- Best Cheap Raspberry Pi Alternatives in 2025
- 1440p Gaming PC Build 2026: Cost, Parts, FPS
- GPT-5.6 Sol Now Requires US Government Approval Per Customer
- Athlon XP + Radeon 9800 Pro AGP Build Guide: 2003 Period-Correct Rig
- Best 4K Monitor for PS5 and Xbox Series X Console Gaming in 2026
- gpt-oss 20B vs Phi-4 14B on a 12 GB GPU: Which One Actually Fits?
- Proprietary Models See Your Business: The Case for a Local Ryzen + RTX 3060 Rig
- retrorecs.com: A New Retro Game Recommendation Engine
Earliest SpecPicks reviews
Browse full archive →- Best GPU for Llama 3.1 8B (2026)
- Best GPU for Qwen 3 14B (2026)
- Best GPU for Qwen 3 32B (2026)
- Best GPU for Llama 3.1 70B (2026)
- Best GPU for DeepSeek-R1 32B (2026)
- Best GPU for Llama 3.1 405B (2026)
- How to run Llama 3.1 8B on NVIDIA GeForce RTX 5090
- How to run Qwen 3 14B on NVIDIA GeForce RTX 5090
- How to run Qwen 3 32B on NVIDIA GeForce RTX 5090
- How to run Llama 3.1 70B on NVIDIA GeForce RTX 5090
- How to run DeepSeek-R1 32B on NVIDIA GeForce RTX 5090
- How to run Llama 3.1 8B on NVIDIA GeForce RTX 4090