ASUS ProArt GR1X vs MSI EdgeMesa: Why Two SSD Slots Might Matter More Than AI TOPS

For many buyers, yes. The ASUS ProArt GR1X and MSI EdgeMesa N AI+ have the same NVIDIA RTX Spark chip and the same "up to 1 petaflop FP4" figure, so AI TOPS can't separate them. Storage can. ASUS lists two SSD slots (PCIe 5.0/4.0, up to 4TB); MSI lists a single M.2 PCIe Gen5 x4 slot, up to 4TB. Local AI fills drives quickly: a handful of popular models in two or three versions each can pass 300 GB before you add datasets, video projects or Windows itself. A second slot lets you add capacity, or keep models separate from the system drive, without replacing the drive you bought. Neither box lets you upgrade memory, so storage is one of the few things you can change later.

How do the two storage designs compare?

Source: asus.com ProArt GR1X page and ASUS technical specifications (Sep–Nov 2026); msi.com EdgeMesa N AI+ specification page (accessed 8 Nov 2026). ASUS's own technical page lists a 1TB PCIe 4.0 SSD as included in the base model; the PCIe generation of other configurations isn't confirmed by ASUS.

Neither company publishes how easy it is to open the case and reach the slots, or the M.2 length the slots accept. Before planning an upgrade, confirm the drive size (2230, 2242 or 2280) and whether opening the unit affects the warranty. We can check this for you at quotation.

How much storage does local AI really use?

Model files are large, and people rarely keep only one. Here is an illustrative library built from published file sizes:

• gpt-oss-120b (MXFP4): about 65 GB
• Llama 3.3 70B at 4-bit (Q4_K_M): about 43 GB, and at FP8 about 71 GB
• Qwen3 32B at 4-bit: about 20 GB, and at 8-bit about 35 GB
• gpt-oss-20b: about 14 GB
• A video model such as LTX-2, whose quick-start download is about 66 GiB (roughly 71 GB)

That adds up to about 318 GB by our arithmetic, before Windows, applications, caches, ComfyUI image models, LoRA adapters, retrieval indexes or your own documents. On a 1TB drive, a working library like this takes about a third of the space. If you fine-tune, keep project files or generate video, a single 1TB or 2TB drive can fill within months. The model sizes come from Hugging Face model cards and project READMEs; your own set will differ.

Most people also keep more than one version of a model. You might test a 4-bit and an 8-bit build to compare quality, keep an older version while a new release proves itself, or store a model for the 64GB split and another for the 96GB split. Disk space is how you keep those options open.

Why is a second slot better than a bigger first drive?

A single 4TB drive from the start solves capacity, and the EdgeMesa offers that. A second slot changes how you can grow and organise the machine:

• Add, don't replace. Buy the 1TB or 2TB model now and add a drive later, without cloning Windows or discarding the original SSD.
• Separate system and data. Keep Windows and applications on one drive and models and datasets on the other. Reinstalling Windows then leaves your model library untouched.
• Isolate sensitive data. A business can keep client documents for retrieval on a separate, encrypted drive that can be removed or securely wiped when the unit is retired.
• Spread the wear. Repeatedly downloading and deleting large models, or writing training checkpoints, adds wear to an SSD. A second drive takes some of that load off the system drive.

The trade-off is cost and complexity. You still need to buy the extra drive, and on a small box a second SSD adds a little heat in a tight space. If your library is modest and fixed, a single large drive in either machine is perfectly reasonable.

Memory decides which models you can run. Storage decides how many you can keep, and it's the one part of these boxes you can still change after you buy.

Does SSD speed matter for AI?

Mostly when loading models. Once a model sits in the unified memory, the SSD is idle during generation. Loading speed still adds up if you switch models often. By our calculation, reading a 65 GB model takes at least about 8 seconds at the PCIe 4.0 x4 interface limit and about 4 seconds at PCIe 5.0 x4; real drives and file systems are slower than these ceilings. From a network drive, the same file takes at least about 52 seconds over 10GbE and about 3.5 minutes over 2.5GbE.

That makes a local second drive more practical than relying on a NAS for models you use every day. A NAS still makes sense as a shared library for a team or as a backup copy, and both boxes have 10GbE to make that faster. Gen5 drives load models faster, but for most people capacity matters more than whether the drive is PCIe 4.0 or 5.0.

Where do AI TOPS fit in?

Both makers quote "up to 1 petaflop FP4", and that number comes from the shared NVIDIA chip, so it cannot help you choose between them. NVIDIA's comparable DGX Spark page notes that the same figure is theoretical and assumes sparsity. Chat-style generation speed is set mainly by memory bandwidth, about 300 GB/s by reviewers' calculations, on both. We explain the gap between the headline figure and real speed in why 1 petaflop doesn't tell you how fast your AI will run, and the other easy-to-miss differences in the hidden differences that could cost you later.

Which should you choose?

Choose the box with two slots if you expect your model library to grow, want to separate business data from the system drive, or plan to buy a smaller configuration now and expand later. The single-slot design is fine if you buy the 4TB configuration up front and keep a tidy library, or if most of your data lives on a server or NAS. Either way, choose memory first: 64GB limits which models fit on the GPU at all (reviewers found Windows exposes at most about 55 GB of a 64GB machine to the GPU), and you cannot add memory later. Our guide to choosing memory without the marketing covers that decision, and which one will age better looks at storage over a three-year life.

Buying in Singapore

The ASUS ProArt GR1X is in our ProArt GR1X collection as price on request. ASUS had not published Singapore pricing at the time of writing; our estimate, based on comparable RTX Spark devices and not an official ASUS price, is about S$6,200–7,200 for 64GB/1TB, S$9,000–10,800 for 128GB/2TB and S$10,000–12,000 for 128GB/4TB, including GST. The MSI EdgeMesa N AI+ is not yet listed with us; ask us about availability. For a shared model library on the network, the QNAP TS-464 4-bay NAS is S$1,080 (listed 8 Nov 2026), with 2.5GbE ports, so expect slower loads than a local SSD. Prices change, so ask for a current quotation. Use Request for Quotation on the product page, call (65) 6978 3502, email Sales@sourceit.com.sg or use our contact page.

Frequently asked questions

How many SSD slots does the ASUS ProArt GR1X have? ASUS lists two SSD slots, PCIe 5.0/4.0, with up to 4TB. It doesn't say whether 4TB is per slot or in total, so confirm before planning a large upgrade.

How many SSD slots does the MSI EdgeMesa N AI+ have? MSI lists one M.2 NVMe PCIe Gen5 x4 slot, with up to 4TB.

Can I upgrade the memory later? No. Both use soldered LPDDR5X memory, so choose 64GB or 128GB at purchase. Storage is the main part you can change afterwards.

Is 1TB enough for local AI? For a few models, yes. A library of popular models in two versions each can pass 300 GB, and video, datasets and fine-tuning work grow quickly, so 2TB or more, or room to add a second drive, is safer.

Does a PCIe 5.0 SSD make AI faster? Only when loading models. Generation runs from memory, so the SSD mostly affects how long you wait when switching models.