Waveshare Jetson TX2 NX Development Kit Deep Learning and Edge Computing
Bottom line: The Waveshare Jetson TX2 NX Development Kit Deep Learning and Edge is a specs-and-price decision rather than a crowd-consensus one in the single-board computers category, priced around $561.99 on Amazon as of 2026-10-07. 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 2026-10-07. Price and availability subject to change.
Pros & Cons
Pros
- ✓ Backed by waveshare'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 This kit includes a TX2 NX Module with onboard 16GB eMMC, does not support Micro Memory card. Adopts classic cooling fan appearance, aluminum alloy enclosure, speed up to 5500RPM. Powerful heat dissipation, no worry about the drop in AI performance due to heat dissipation problems. High-quality carrier board to match the strong performance of the TX2 NX Module. Waveshare is widely praised for the board durability and manufacturing quality. We optimize each part of the board with good workmanship and materials. Jetson TX2 NX modules cloud-native support lets developers build…
SpecPicks Verdict
SpecPicks scored Waveshare Jetson TX2 NX Development Kit Deep Learning and Edge… using a rating × review-volume × price-fit model applied to published specs and reviews across the single-board computers category. waveshare'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
- This kit includes a TX2 NX Module with onboard 16GB eMMC, does not support Micro Memory card.
- Adopts classic cooling fan appearance, aluminum alloy enclosure, speed up to 5500RPM. Powerful heat dissipation, no worry about the drop in AI performance due to heat dissipation problems.
- High-quality carrier board to match the strong performance of the TX2 NX Module. Waveshare is widely praised for the board durability and manufacturing quality. We optimize each part of the board with good workmanship and materials.
- Jetson TX2 NX modules cloud-native support lets developers build and deploy high-quality, software-defined features on embedded and edge devices.
- Pre-trained AI models from NGC and the TAO Toolkit give you a faster path to trained and optimized AI networks, while containerized deployment to Jetson devices allows flexible and seamless updates.
Full Specifications
| ASIN | B0BJ6X3WVL |
|---|---|
| Brand | waveshare |
| Model Name | Jetson TX2 NX |
| Manufacturer | Waveshare |
| Model Number | JETSON-TX2-NX-DEV-KIT-US |
| Mfr Part Number | JETSON-TX2-NX-DEV-KIT-US |
| Processor Brand | NVIDIA |
| Compatible Devices | Linux-based devices, Docker-compatible devices |
| RAM Memory Installed | 16 GB |
| Wireless Compability | Bluetooth |
| RAM Memory Technology | LPDDR4 |
| Connectivity Technology | Bluetooth |
| Memory Storage Capacity | 16 GB |
| Ram Memory Installed Size | 16 GB |
Ready to buy?
Waveshare Jetson TX2 NX Development Kit Deep Learning and Edge Computing 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 2026-10-07. Price and availability subject to change.
Related Single-Board Computers
Waveshare Jetson TX2 NX Development Kit Deep… 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 →- Emulation Hardware in 2026: FPGA, Software, and Cart-Reader Ecosystems
- Best Budget Gaming PC Build 2026 — ~$1,000 ($800 on Sale)
- How to Build a Windows 98 Retro PC in 2026
- RTX 4070 Super vs RX 7800 XT — Which to Buy in 2026
- Best 1440p Gaming GPUs in 2026
- The Complete Voodoo5 5500 AGP Driver Guide (2026 Edition)
- Best Retro Handhelds in 2026 — From $35 to $500
More reviews from the SpecPicks archive
Browse all reviews →- Best 1TB SATA SSD for Cloning Old Drives and OS Migrations 2026
- Intel Arc Pro B70 (BMG-G31) Posts Strong Linux Gaming Numbers — How It Stacks Up Against an RTX 3060
- Gemini 3.5 Flash vs Local LLMs on a 12GB GPU: When Cloud Wins
- Building a 2001 Pentium III + GeForce 3 Win98SE Gaming Rig: A 2026 Build Log
- Intel Arc B580 LLM Inference: 12GB Battlemage Benchmarks
- Building a Budget Sim Racing Setup: Logitech G920 vs Thrustmaster TH8A Shifter
- Best GPU for 1080p Esports in 2026: Why the RTX 3060 12GB Still Delivers
- CompactFlash + IDE Storage for a Period-Correct Windows 98 Build
- Best CPU Cooler for the Core i7-9700K in 2026
- 4K Mini-LED vs 240 Hz QD-OLED: Which Monitor for Work and Play?
- When Does a Homelab Become a Job?
- Qwen3 MTP on a Single RTX 3060 12GB: What the New Benchmark Numbers Actually Mean
- AI Bug-Hunting Surged: Running a Local Security-Scanner LLM on 12GB VRAM
- This Open-Source KVM Runs a Pentium 4 Instead of a Raspberry Pi
- Ollama on the RTX 3060 12GB: Model Sizes and tok/s for 2026
- How to run Llama 3.1 8B on AMD Radeon RX 7900 XTX
- RTX A6000 48GB vs RTX 3090 24GB for Production LLM Inference (2026)
- Best Gaming Monitor for Console + PC Dual Setup in 2026
- Best SATA SSD for an AM4 Budget Build: BX500 vs 870 EVO vs WD Blue
- RTX 3060 12GB vs RTX 3060 Ti 8GB for Local LLMs: VRAM Beats Bandwidth Every Time
- hipEngine on Strix Halo + 7900 XTX: Native Qwen 3.6 Inference Without ROCm Drama
- Anthropic's 2GW AMD Deal: What It Means for Local-vs-Cloud Builders
- Stable Diffusion vs Flux — which open image model wins in 2026?
- What Hardware Runs a Gemini-Class Model Locally in 2026?
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