How much does an AI server cost? Prices by tier in 2026

The price of a server for AI depends on the tier, the number of cards and the memory, and in 2026 the memory shortage is pushing everything upward. Here are indicative ranges by segment.

By QDNA · Published on 18 July 2026 · Updated on 7 September 2026 · 9 min read

What sets the price of an AI server?

Three factors dominate: the number and type of graphics cards, the amount of memory, and the server form factor, with memory weighing more than ever in the total. The full calculation, hardware versus pay-per-token, is in our article on-premises versus API cost.

Memory, the driver of 2026 prices

Manufacturers have redirected their capacity toward high-bandwidth memory for AI accelerators, which yields more revenue per wafer than standard memory, and the result is a scarcity of ordinary system memory.

Over one year, server memory prices have risen sharply, and Dell warned its customers of increases of at least 15% to 20% from mid-December 2025, while Lenovo let all of its quotes expire on 1 January 2026 (TrendForce, 5 December 2025). A workstation such as the DGX Spark saw its price rise from around four thousand to nearly four thousand seven hundred dollars, purely because of memory cost, and relief is not expected for several years.

Price ranges by tier

The figures below give order-of-magnitude estimates for 2026, taxes and integration excluded, and they are deliberately wide since configuration and memory can double the total.

These prices are indicative and non-contractual, estimated for 2026 excluding discounts, hosting and integration, with precise pricing depending on the configuration chosen. Dollar figures are converted at the ECB rate of 1 September 2026 (€1 = $1.159) and move with it, so the euro column is the reference.

Turnkey appliance or identifiable hardware?

Alongside the reference hardware listed above sits a second category, the private AI appliance sold as a sealed box with its own software stack. These vendors publish no list price: Zanus AI, one of the better-known names in the segment, shows three tiers on its own site with a quote request button where the price would be.

Third-party estimate sites fill the gap, and their figures for the same tier vary by nearly a factor of three, which says enough about what they are worth.

The ranges on this page take the opposite approach, since they are tied to identifiable hardware and can therefore be checked line by line against a quote: this many cards, this much memory, this chassis. An appliance price that cannot be decomposed cannot be compared, and that is the only reason we publish wide ranges rather than one reassuring number.

Hardware partners

The calculation relies on NVIDIA graphics cards, and servers are certified by HPE, Dell, Supermicro, Lenovo, ASUS, and Gigabyte, which brings the vendor support and warranty expected in enterprise settings. Dell and Lenovo notably raised their server prices as soon as the shortage began.

QDNA integrates and operates this hardware from workstation to rack, and detailed tiers are in our hardware sheets.

Should you buy, colocate, or rent an AI server?

Three paths coexist: buying ties up capital but amortizes the cost over several years, with a cost per token close to zero, while managed colocation in a sovereign French data center avoids buying premises and keeps legal control, and renting capacity suits peaks or validation, ahead of an investment.

The cost break-even point is detailed in the article on-premises versus API cost.

The market is moving AI on-premises

The market is indeed moving AI on-premises. A survey published by Cloudian in March 2026 among 203 IT decision-makers finds that 93% of enterprises are already repatriating AI workloads from the public cloud, are in the process of doing so, or are actively evaluating it, and that 79% have already moved some.

The same year, Broadcom's Private Cloud outlook, a survey of 1,800 senior IT leaders across eight countries, reports that 83% of leaders are considering repatriation, up from 69% a year earlier. The question of on-site price takes on concrete meaning as those workloads come back home.

The reasons overlap from one study to the next. The Cloudera survey conducted in 2024 among six hundred IT leaders places security and compliance at the top of the barriers (74%), ahead of the lack of skills to manage the tools (38%) and their cost (26%). Control over proprietary data, billing predictability, and legal sovereignty recur as the three drivers of this shift.

Over time, the financial trade-off follows the same slope. For a sustained workload, a purchased and amortized server keeps a cost per token well below usage-based billing, and the three-year total cost of ownership can come in below equivalent cloud billing, which the calculation below lets you check rather than assume. This does not condemn hosting, which stays relevant for peaks and validation phases, in a hybrid approach. It clarifies why the price of a server, measured against real usage, reads as an investment rather than an expense.

Sizing correctly before buying

Model size and number of users set the tier, since a compact model fits on a workstation while a large model requires a server. The practical guide is in deploying a local LLM. In a tight memory market, correct sizing avoids overpaying for an oversized configuration.

How to compare the real cost per token?

The purchase price does not tell the whole story. What matters is the cost per token, which depends on hardware throughput for a given model. The open comparator InferenceX by SemiAnalysis publishes reproducible, auditable measurements: latency, throughput in tokens per second, and implied cost per token.

It pits accelerators against each other in pairs, from the H100 and H200 to the Blackwell B200, B300, GB200 NVL72 and GB300 NVL72 and the RTX PRO 6000, against AMD MI300X, MI325X and MI355X cards. The measurements cover about ten representative open-weight models, including DeepSeek V4 Pro, Kimi K3 and K2.7, GLM 5.3, MiniMax M3, Qwen 3.8 Flash Next, gpt-oss and Llama (list re-read on 2 September 2026).

The useful takeaway for a buyer comes down to a rule the spec sheet never shows on its own: the cost per token depends on the throughput achieved on the target model, so the hardware is chosen from the real workload rather than from the sticker price. A more expensive accelerator that delivers more tokens per second frequently costs less per token, once the pairwise comparison verifies this economics card against card, on the exact model the organisation intends to serve in production.

Cost per million tokens: what can be calculated and what remains to be measured

The cost per token depends on the model served and on the throughput achieved, and it cannot be guessed: it is calculated from four named assumptions, hardware price excluding VAT amortised over 1,095 days, electrical power, price per kilowatt-hour, and aggregate throughput published by a third party for the target model.

The table therefore only keeps the machines for which such a throughput exists for DeepSeek V4 Flash, and the full calculation, formula, assumptions, sources and worked numbers, is in our DeepSeek V4 Flash 0731 versus APIs comparison.

The first line in full: 4,875 / 1,095 = €4.45 of amortisation a day, plus 0.24 kW × 24 h × €0.1624/kWh = €0.94 of electricity, i.e. €5.39 a day; at 30 tokens/s and 30% load, the machine produces 30 × 86,400 × 0.30 = 777,600 tokens a day, hence 5.39 / 0.778 = €6.93 per million. DeepSeek's own price list bills the same model at $0.44 to $0.88 per million (2 September 2026) and Claude Opus 5 costs $15 per million: a local workstation drops below closed APIs from a few hundred thousand tokens a day, and only drops below the vendor's price list as a heavily loaded cluster. Per-card throughput can be checked on the InferenceX comparator by SemiAnalysis.

References

• NVIDIA DGX Spark Founders Edition on the idealo.fr price comparator (listing of 2 September 2026)
• NVIDIA DGX Spark Founders Edition on the idealo.fr price comparator (listing of 2 September 2026)
• NVIDIA DGX Spark Founders Edition on the idealo.fr price comparator (listing of 2 September 2026)
• NVIDIA DGX Spark Founders Edition on the idealo.fr price comparator (listing of 2 September 2026)
• NVIDIA DGX Spark Founders Edition on the idealo.fr price comparator (listing of 2 September 2026)
• NVIDIA DGX Spark Founders Edition on the idealo.fr price comparator (listing of 2 September 2026)
• DGX Spark price increase, Tom's Hardware
• RTX PRO 6000 pricing, Tom's Hardware
• HBM3E price hike 2026, TrendForce
• InferenceX inference comparator, SemiAnalysis
• AI server cost breakdown, SemiAnalysis
• Enterprise AI Infrastructure Survey 2026, Cloudian
• Private Cloud Outlook 2026, Broadcom
• State of Enterprise AI 2024, Cloudera
• Dell increases of 15% to 20% and Lenovo quote expiry, TrendForce (5 December 2025)
• DGX Station GB300, prices per OEM excl. VAT, pi3g (page dated 27 August 2026)
• Mac Studio M5 Ultra, Apple Store France (read on 2 September 2026)
• DGX Spark specification sheet, 240 W power supply, NVIDIA
• DGX Station specification sheet, 1,600 W, NVIDIA
• CRE deliberation 2026-147 of 15 July 2026, regulated tariffs from 1 August 2026
• DeepSeek V4 Flash throughput on one DGX Spark, NVIDIA forum (15 July 2026)
• DeepSeek V4 Flash 0731 throughput on two DGX Spark, Classmethod (10 August 2026)