NVIDIA publishes no DGX Station price. Here is every OEM listing, the Windows model, what it costs per month, and what else buys you serious local AI capacity.
The DGX Station has no official price. Public US listings start at $92,887.47, most sit between $96,000 and $130,000, Dell's lists at $159,283, and storage, add-on GPUs and service push quotes higher. Here is what the price really covers, what else buys you serious local AI capacity, and the uncomfortable reason most of the cheap alternatives got expensive too. If you are still working out which DGX you need, start with our NVIDIA DGX alternatives overview, and if you meant the small one, see DGX Spark alternatives.
DGX Station price: what each OEM charges (October 2026)
| DGX Station system | Public US price | Status (checked on 2 Nov 2026) |
|---|---|---|
| Supermicro Super AI Station (Gold Series ARS-511GD-NB-LCC-01-G2) | from $92,887.47 before tax and shipping | Supermicro's eStore (price as reported by TechRadar) |
| Exxact Valence VWS-158270643 | $96,250 starting price | Configure-to-order, quote button; Linux, preloaded with DGX OS on Ubuntu |
| MSI XpertStation WS300 | $99,999 | Newegg, out of stock |
| Gigabyte W775-V10-L01 | $116,999 | Newegg, out of stock |
| Bizon GB300 AI Station | $122,159 | In stock, ships in 10 to 14 days |
| ASUS ExpertCenter Pro ET900N G3 | $123,375 to $129,827.99 | Resellers (CyberPowerPC, AVADirect, CDW); CyberPowerPC quotes about 8 weeks |
| Dell Pro Precision with GB300 | $159,283 | dell.com; checkout showed "not currently available" |
| HP ZGX Fury G1n AI Station | quote | Fixed SKUs through HP and resellers |
Every one of these carries the same GB300 superchip and the same 748GB of coherent memory. What changes the price is everything around it.
What about DGX Station for Windows? Every listing above is the Linux version running NVIDIA DGX OS. The Windows version has no price or date yet; see the next section.
What is the DGX Station price in India? We found no Indian price from NVIDIA or the OEMs themselves, but MSI's XpertStation WS300 is listed by Indian retailers. On 22 October 2026 NationalPC listed it at ₹1,44,05,932.20 plus 18% GST (₹1,69,99,000, about ₹1.7 crore), open for pre-booking with a 25% deposit, and PC Studio listed it at ₹1,49,99,990 including taxes. ModX Computers (₹1,44,53,990) and Computech Store showed it out of stock. For other versions, ask an Indian reseller for a quote.
What "DGX Station price" actually means. NVIDIA supplies the GB300 board and partners build the workstation around it, so there are at least six prices, not one. A listed figure is a base configuration. Storage, an optional RTX PRO card for display and graphics work, warranty length and on-site service are all extras. The European distributor pi3g quotes the same family from about $99,000 to $194,500 depending on vendor and configuration, with lead times of two to sixteen weeks as of mid-September.
Costs that are not on the invoice. NVIDIA rates total system power at 1,600 W. Bizon notes the power supply tops out around 1,300 W on a standard 100 to 114 V, 15 A outlet, so the full 1,600 W needs a 115 to 240 V circuit. Budget for an electrician before the machine arrives. Exxact also offers education and government pricing, which is worth asking every vendor about.
When a vendor will not print the price, the price is the feature they are least proud of. The practical move is to get two or three OEM quotes on an identical configuration, because the spread between them is larger than any discount you will negotiate on one.
Where to buy a DGX Station
You can't buy one from NVIDIA. Order through an OEM's own store (Supermicro, Dell, HP) or configurator (Exxact, Bizon), or through resellers such as Newegg, CDW, CyberPowerPC and AVADirect, which carry the MSI, Gigabyte and ASUS builds. Most listings are quote or configure-to-order, so ask each vendor for the same configuration, the lead time in writing and education or government pricing if it applies.
DGX Station for Windows: price and availability
DGX Station for Windows was announced at Computex 2026 and previewed at NVIDIA's 7 October 2026 Windows event, with ASUS, Dell, GIGABYTE, HP, MSI and Supermicro as partners. It runs on the same GB300 Grace Blackwell Ultra Desktop Superchip, with 748GB of coherent memory and up to 20 petaFLOPS of FP4.
NVIDIA has published no price and no release date; press reports point to Q4 2026. The product page only offers a sign-up to be notified when it is available. The roughly $92,900 to $96,250 listings you may see quoted are for the Linux DGX Station running DGX OS on Ubuntu, not the Windows version. No Windows DGX Station is listed or priced anywhere yet.
How much does a DGX Station cost per month?
Spread the cheapest listing, $92,887.47, over 36 months and the DGX Station costs about $2,580 a month before power, storage or support. Power adds roughly $110 to $130 a month if it runs flat out around the clock at Bizon's measured 1,000 to 1,200 W full load, or about $175 at NVIDIA's 1,600 W rating, at an assumed $0.15 per kWh. The same $2,580 rents about 386 hours a month of an on-demand B200 at Lambda ($6.69 per GPU-hour), or about 372 hours of a B300 on RunPod's Community Cloud ($6.94), roughly half of every hour in the month.
What a DGX Station is
The DGX Station is NVIDIA's desktop workstation built around the GB300 Grace Blackwell Ultra Desktop Superchip: a 72-core Grace CPU on Arm Neoverse V2, fused to a Blackwell Ultra GPU over NVLink-C2C.
The number that matters is memory: 748GB of coherent memory, made up of 252GB of HBM3e running at 7.1 TB/s plus 496GB of LPDDR5X on the Grace CPU. (It's often searched as 768GB or 784GB; the figure NVIDIA publishes is 748GB.) For reference, an H200 does 4.8 TB/s. NVIDIA rates it at up to 20 petaFLOPS of FP4. It also carries a ConnectX-8 SuperNIC at up to 800 Gb/s, which lets you link two Stations, and it supports MIG partitioning into as many as seven isolated instances.
NVIDIA pitches it at the trillion-parameter model class. That is not marketing inflation. It holds models nothing else on a desk can hold.
Wait. Do you mean the Station or the Spark?
This trips up a surprising number of people, and getting it wrong costs you either $92,000 or a machine that cannot do the job.
DGX Spark is the small one. GB10 Superchip, 128GB of LPDDR5X unified memory, roughly 273 GB/s of bandwidth, about 1 petaflop of FP4. It launched at $3,999 in October 2025, was raised to $4,699 in late February 2026 and to $6,950 on 2 October 2026, with NVIDIA citing memory supply both times. A 64GB version costs $4,999 and has been on sale since 23 October.
DGX Station is the workstation. GB300, 748GB of coherent memory, HBM3e at 7.1 TB/s, and a price roughly twenty times higher.
They are not competitors and they do not share an alternatives list. A Spark buyer is asking "can I prototype locally instead of burning cloud credits." A Station buyer is asking "can I hold a trillion-parameter model in my building." If you meant the smaller machine, our DGX Spark alternatives breakdown covers that comparison properly.
Here is where it gets messy. Almost everything positioned as a "DGX alternative" online is really a Spark alternative. Nothing under $20,000 replaces a Station on capacity. What the cheaper options do is let you ask whether you needed that capacity at all.
Why every DGX Station alternative got more expensive
A friend sent me a screenshot on Tuesday. NVIDIA's own marketplace, RTX PRO 6000 Blackwell, 96GB. Sixteen thousand dollars.
He had built his hardware budget in a spreadsheet eleven months earlier, when that same card listed at $8,565. His whole plan, the one where he skipped the DGX Station and bought two workstation cards instead, had quietly doubled in price while he was busy getting approvals.
That is the actual state of this decision in 2026, and it is why most DGX Station alternative comparisons you will find are wrong. They were written against 2025 prices. The memory shortage moved every number on the board, and it did not move them evenly.
So here is the honest version: what the DGX Station costs, what the six real alternatives cost right now, and the case for not buying any of them. This page covers the DGX Station specifically. For the whole family (Spark, Station and the rack tiers), see our NVIDIA DGX alternatives overview.
DGX Station alternatives (2026): 6 options ranked by cost
The cheapest credible DGX Station alternative is the RTX PRO 6000 Blackwell 96GB at about $16,000, and for most agent teams the honest alternative is not buying a workstation at all. If your agents call hosted models anyway, BetterClaw's Free plan runs cloud agents with no hardware at all, on your own API key.
Prices below reflect street prices, not launch MSRPs. Verify before you buy; they have moved monthly.
| Option | Memory | Bandwidth | Price now | Launch price |
|---|---|---|---|---|
| NVIDIA DGX Station (GB300) | 748GB coherent | 7.1 TB/s (HBM3e) | $92,887.47 to $159,283 listed, more as configured | never published |
| RTX PRO 6000 Blackwell 96GB | 96GB GDDR7 | 1.79 TB/s | $16,000 to $17,999 | $8,565 |
| NVIDIA DGX Spark | 128GB LPDDR5X | 273 GB/s | $6,950 (64GB: $4,999) | $3,999 |
| Mac Studio M5 Ultra | up to 512GB | 1.2 TB/s | from $5,499 | from $5,499 |
| Strix Halo 128GB mini PC | 128GB unified, ~96GB GPU-addressable | 256 GB/s | $3,099 to $4,349 | ~$1,999 |
| RTX 5090 multi-GPU build | 32GB per card | 1.79 TB/s | from about $4,800 per card | $1,999 |
| Cloud rental (B200 on demand) | 180GB per GPU | full HBM | $6.69 to $6.99 per GPU-hour at Lambda | n/a |
Look at the launch price column. Almost every owned option costs more than it did at introduction, and the RTX 5090 sells for more than double its launch price. The Mac Studio only escapes because it launched in August at post-shortage prices. Rental is the only column that didn't punish you for planning ahead.
RTX PRO 6000 Blackwell 96GB: the alternative that stopped being obvious
For most of 2025 this was the easy answer: 96 gigabytes of GDDR7 with ECC in a single slot, 24,064 CUDA cores, 1.79 TB/s, in a workstation you already owned.
Then it went from $8,565 at launch to $13,250 in June 2026 to $16,000 on NVIDIA's marketplace by August, where it still sits. Roughly 87 percent up. Retail listings followed: Newegg's US-shipped Workstation Edition cards ran $16,699.99 to $16,999 and B&H listed versions from $16,999 to $17,999 in mid-October. The cause is the GDDR7 shortage: its 96GB clamshell design is the largest VRAM pool on any discrete GPU, which makes it the most supply-sensitive product in the category.
Worth knowing: it has the same 1.79 TB/s bandwidth as an RTX 5090. You are buying capacity and slot count, not speed.
Mac Studio M5 Ultra: the ceiling came back
For most of 2026 the Mac Studio was a cautionary tale: Apple pulled the 512GB M3 Ultra configuration in March, the 256GB tier in May, and raised prices in June, all blamed on memory supply. Then on 25 August 2026 Apple announced the M5 Max and M5 Ultra Mac Studio and discontinued the M3 Ultra.
The 512GB ceiling is back, at 1.2 TB/s, roughly four and a half times a DGX Spark's 273 GB/s. Pricing starts at $5,499 for 96GB, and 256GB with 2TB of storage is $11,299 on Apple's store. Deliveries began 22 September; the 512GB configuration was expected from late October. Apple also says four machines can be clustered over Thunderbolt 5 with RDMA into one shared memory pool.
That makes it the cheapest way to hold a very large model in unified memory on a desk. The caveats: no CUDA, so your local stack won't mirror a cloud deployment, and memory upgrades above the base are expensive. More in Apple Silicon versus NVIDIA for AI workloads.
DGX Spark: the CUDA parity play
At $6,950 the Spark is not fast. Its 273 GB/s bus is the bottleneck, and dense 70B decode lands in single digits with common tooling. What it buys is software: the full CUDA and TensorRT-LLM stack your cloud instances run, so what works on your desk works in production. NVIDIA's CES 2026 software update delivered up to 2.5x over launch performance. Buy it as a development box, not an inference server.
Strix Halo 128GB mini PCs: the capacity bargain that also inflated
The AMD Ryzen AI Max+ 395 puts 128GB of unified LPDDR5X in a lunchbox-sized machine, with roughly 96GB addressable as GPU memory on Linux. Early in 2026 a 128GB Framework Desktop cost $1,999. In October the 128GB tier ran from $3,099 (Bosgame M5, 2TB) through $3,649.99 (GMKtec EVO-X2, 2TB) to $4,349 (Beelink GTR9 Pro), with Framework's $3,449 build out of stock. Bandwidth is 256 GB/s: run big models slowly and privately, and stay on Linux, because Windows costs 20 to 30 percent throughput.
RTX 5090 multi-GPU: the DIY route
Same 1.79 TB/s as the PRO 6000, 32GB per card, launched at $1,999. In October new cards on Newegg started around $4,800 and marketplace sellers asked $8,000 to $9,600. Four of them give you 128GB of pooled VRAM for a little more than one PRO 6000, plus a power, thermal, chassis and tensor-parallelism problem. Good value if your time is cheap and your electrician is friendly.
Renting DGX-class hardware instead of buying it
Lambda rents an on-demand B200 (180GB of HBM per GPU) for $6.69 to $6.99 per GPU-hour depending on instance size, and an H100 SXM from $3.99. Take the cheapest DGX Station listing, $92,887.47: at $6.69 an hour that is about 13,900 GPU-hours, about nineteen months of never turning it off. And you rent current data-center silicon rather than owning a desktop part that will be a generation behind when the DRAM crunch eases.
Buying wins on three things: data that legally cannot leave your building, workloads that run continuously at high utilization, and latency-sensitive interactive work.
Everything else is a preference dressed as a requirement. We ran the same exercise for the smaller machine in DGX Spark cloud rental versus buying, and the answer came out the same way.
Do you need a DGX Station for AI agents?
A lot of people pricing a DGX Station tell me they need it "for AI agents." Almost none of them do. An autonomous agent spends its life on orchestration, tool calls, memory lookups and API round trips. The model inference is usually a hosted API call. The bottleneck is scheduling and context management, not local FLOPs.
Local silicon matters when the weights must stay in the room. It doesn't matter for most agent work, and conflating the two is how hardware budgets get approved for problems they don't solve.
Picking a DGX Station alternative by what you are actually doing
Training or fine-tuning trillion-parameter models on premises, with data that cannot leave: buy the DGX Station. Get quotes from at least two OEMs and accept a 2 to 16 week lead time.
70B to 120B inference locally for a small team: RTX PRO 6000 96GB, or Strix Halo if capacity and privacy beat throughput; Mac Studio M5 Ultra (up to 512GB) if you need more than 96GB.
Developing against CUDA to match your cloud deployment: DGX Spark.
Private AI for a team with no ML engineers: a turnkey appliance with the software preinstalled, such as the servers in our Zanus AI review. You trade published specs and a resale market for one vendor that runs the whole stack.
Bursty research that spikes and idles: rent. Ownership rarely wins below about 60 percent utilization.
Building AI agents rather than training models: no workstation. Start with the orchestration layer; see local model hardware for agent workloads.
The most expensive hardware mistake in 2026 isn't buying the wrong box. It's buying any box for a workload that was never compute-bound.
What I would tell a friend with the purchase order open
Don't benchmark this decision against last year's prices. That is the whole lesson of 2026.
The DGX Station is a remarkable machine, and a narrow set of teams should buy one without hesitation. If you hold regulated data and need a trillion-parameter model in your own building, the alternatives aren't alternatives; they're compromises with a different shape.
For everyone else, the shortage forced a useful question: do you actually need to own the compute, or did owning it just feel more serious than renting it? My friend with the spreadsheet ended up renting for six months while he found out. He hasn't gone back to the purchase order.
Frequently Asked Questions
What is the NVIDIA DGX Station price?
NVIDIA doesn't publish one and doesn't sell a Founders Edition, so prices come from OEMs. The cheapest public US listing is Supermicro's Super AI Station at $92,887.47 before tax and shipping. Exxact starts at $96,250, the MSI XpertStation WS300 is $99,999, Gigabyte, Bizon and ASUS builds run $116,999 to $129,827.99, and Dell lists at $159,283. Storage, an add-on GPU and service push quotes higher.
How much does a DGX Station cost per month?
About $2,580 a month if you spread the cheapest $92,887.47 listing over 36 months, plus roughly $110 to $175 a month in power if it runs around the clock. The same money rents about 386 hours a month of an on-demand B200.
Is there a DGX Station for Windows, and what does it cost?
NVIDIA announced it at Computex 2026 and previewed it on 7 October 2026, but it has no published price or release date; press reports point to Q4 2026. Every DGX Station you can price today is the Linux version running DGX OS.
Where can I buy a DGX Station?
From OEMs and resellers, not NVIDIA: Supermicro, Dell and HP sell directly, Exxact and Bizon through configurators, and MSI, Gigabyte and ASUS builds through Newegg, CDW, CyberPowerPC and AVADirect. Lead times run from about two to sixteen weeks.
How much memory does the DGX Station have?
748GB of coherent memory: 252GB of HBM3e at 7.1 TB/s plus 496GB of LPDDR5X. You may see it searched as 768GB or 784GB, but 748GB is NVIDIA's figure.
What is the best DGX Station alternative?
The RTX PRO 6000 Blackwell 96GB at about $16,000 is the cheapest credible one. For capacity, the Mac Studio M5 Ultra (up to 512GB, from $5,499) is the closest desktop, without CUDA. For trillion-parameter work nothing under $20,000 substitutes; renting B200-class GPUs is the closer match.
How does the DGX Station compare to the DGX Spark?
Different machine classes. The Spark uses the GB10 with 128GB at about 273 GB/s for $6,950 (64GB: $4,999); the Station uses the GB300 with 748GB and HBM3e at 7.1 TB/s from $92,887.47. The Spark is a development box; the Station is a workstation-class compute machine.
Is renting DGX-class hardware cheaper than buying?
For most teams, yes. At $6.69 per B200 GPU-hour, the cheapest DGX Station equals about 13,900 GPU-hours, more than a year and a half of continuous use. Buying wins mainly when data can't leave your premises or utilization stays above about 60 percent.
Do I need a DGX Station to run AI agents?
Almost certainly not. Agents spend their time on orchestration, tool calls, memory and API round trips, not local inference. Unless your model weights must stay in your building, a managed agent platform with your own API keys removes the hardware question.
