Dedicated GPU Infrastructure for AI: Get the Right Hardware Without the Wait
Demand for dedicated GPUs keeps rising as more companies scale up AI projects. Datalok draws on its own GPU stock and a network of datacenter operator partners to connect you with the right capacity, quickly.
Direct access to dedicated GPU capacity, without the usual detours
Teams looking for that capacity tend to run into the same obstacles: lead times that keep stretching with traditional suppliers, uncertain availability, and sometimes several intermediaries to get through before reaching a concrete answer.
Whether your project calls for a full GPU rack, a handful of dedicated servers, or a custom configuration, Datalok draws on its available stock and partner network to identify the option that fits your technical requirements, timeline, and budget. This dual approach shortens lead times considerably compared with a traditional supplier search. Pricing stays transparent and gets negotiated directly between the parties involved.
How the matching process works
Three steps are all it takes to identify the right source of GPU capacity.
Describe your need
The type of AI workload, the compute power you're after, any location constraints, and your project timeline.
Qualification by the Datalok team
Identifying the most relevant source, whether that's Datalok's own stock or a partner in the network.
Direct introduction
No added layer of intermediation; the contract gets settled between your company and the chosen supplier.
Who this is for
This offer fits a range of profiles, all facing the same constraint: getting reliable GPU capacity, fast.
Research labs
Training their own models.
Scale-up startups
That can no longer find a slot with their usual suppliers.
Systems integrators
Deploying AI projects for their clients.
Cloud repatriation
Companies regaining control over their AI infrastructure costs.
Public-sector organizations
Working on digital sovereignty projects.
Why work with Datalok
- An already-vetted partner network, so there's no need to check each potential supplier's reliability yourself
- Pricing with no hidden margin from a stack of intermediaries
- Help sizing the request upfront, to avoid over- or under-provisioning
- No fixed-term commitment imposed by a single middleman: it's the contract signed with the chosen supplier that sets the terms
Brands and models available
Datalok's stock and partner network cover the main GPU generations used for AI, from NVIDIA, AMD, and Intel. Exact availability by model depends on timing and volume requested; the Datalok team confirms real access once your request has been qualified.
| Brand | Model | Recommended use |
|---|---|---|
| NVIDIA | H100 | Still the most widely deployed option for training and inference on large models, available as a single server or a full rack. |
| NVIDIA | H200 | An extended version of the H100 with more onboard memory, suited to demanding inference workloads and long context windows. |
| NVIDIA | B200 | The Blackwell generation, for projects that need the highest compute power on the market, subject to availability. |
| NVIDIA | B300 | The Blackwell Ultra generation, with greater memory and compute power than the B200, for the most demanding training and inference workloads. |
| NVIDIA | GB200 NVL72 | A full NVLink-interconnected Blackwell rack, for training models at very large scale. |
| NVIDIA | GB300 NVL72 | The Blackwell Ultra evolution of the GB200 NVL72, for the most recent very large-scale deployments. |
| NVIDIA | L40S | Geared toward inference, rendering, and mixed AI/visualization workloads, a solid alternative when large-scale training isn't the priority. |
| NVIDIA | A100 | Still present with some partners for existing deployments or less latency-critical needs. |
| NVIDIA | DGX (DGX B200, DGX H100…) | Turnkey NVIDIA DGX server platforms, available depending on the configuration selected. |
| AMD | Instinct MI300X / MI325X | An alternative to the NVIDIA ecosystem, with onboard memory well suited to large models and long context windows. |
| AMD | Instinct MI350X / MI355X | AMD's most recent generation, for projects comparing options before committing. |
| Intel | Gaudi 2 / Gaudi 3 | Intel's AI accelerators, an alternative worth considering for large-scale training and inference. |
| Intel | Data Center GPU Max Series | Intel's GPU for intensive computing and AI, for projects looking to diversify their sourcing. |
If your project requires a specific model or brand, mention it when describing your need: it speeds up qualification and matching with the right source.
Looking for a hosting site for your own AI servers instead? Visit our AI-ready datacenters page.
Frequently Asked Questions
What kinds of AI projects can benefit from dedicated GPUs through Datalok?
Model training, large-scale inference, scientific computing, and 3D rendering are among the most common use cases seen on the Datalok marketplace.
What's the difference between a dedicated GPU and a cloud GPU instance?
A dedicated GPU is reserved for a single customer, on a server or rack that's exclusively theirs, which gives more predictable performance and cost over time. A cloud instance is shared and billed by usage, offering more flexibility but less budget predictability for sustained workloads.
How long does it take to get matched with a supplier?
Timing depends on the configuration requested and current availability, but the goal is to shorten the lead times typically seen with traditional suppliers, thanks to Datalok's own stock and an already-identified partner network.
Does Datalok only offer GPU capacity in France?
No. Datalok's partner network covers France and several European countries, and extends further depending on the project.
Which GPU models does Datalok offer?
Datalok's stock and partner network cover the main NVIDIA ranges (H100, H200, B200, B300, GB200 NVL72, GB300 NVL72, L40S, A100, DGX configurations) as well as AMD Instinct GPUs (MI300X, MI325X, MI350X, MI355X) and Intel AI accelerators (Gaudi 2, Gaudi 3, Data Center GPU Max Series). Exact availability by model is confirmed once your request has been qualified.
Let's talk about your GPU project
Describe your need (workload type, model or brand you're after, timeline) through our contact form. The Datalok team identifies the right fit from its own stock or partner network.