GPU / compute platforms companies, products & suppliers

GPU and accelerator capacity for training or inference, not a model product. Jobs: gpu vms; reserved clusters; multi-node training fabric.

What are GPU / compute platforms?

GPU and accelerator capacity for training or inference, not a model product. Jobs: gpu vms; reserved clusters; multi-node training fabric.

What problems does it solve?

Teams cannot get compliant accelerators at the region and tenancy they need.

Typical business use cases

  • GPU VMs
  • Reserved clusters
  • Multi-node training fabric

Important capabilities

  • Accelerator types
  • Regions
  • Orchestration

What buyers should evaluate

  • Region
  • Tenancy
  • Data gravity

Risks and governance considerations

Training data sitting on someone else's GPU without isolation.

Procurement checklist

  • Isolation
  • Region
  • Exit of data

Relevant AI Trustmark assurance

AI Trustmark independent findings appear only when an assessment or certificate exists. Category membership does not imply verification.

Methodology · How verification works

Companies and providers

Claimed suppliers appear first so buyers can start with listings the company has taken ownership of. Payment does not buy this order.

  • CoreWeave

    CoreWeave is the force multiplier that empowers pioneers with momentum, magnitude, and mastery—enabling them to innovate with confidence. CoreWeave publishes CoreWeave GPU Compute

  • Crusoe

    Crusoe provides next-gen AI infrastructure and cloud compute using an energy-first approach. Deploy AI workloads at scale with reliable performance and 24/7 support. Crusoe publish

  • CUDO Compute

    CUDO Compute designs, commissions and operates production AI infrastructure. We secure land, provision power and deploy NVIDIA GPU clusters to deliver environments engineered for l

  • Fluidstack

    We build compute faster than anyone on the planet. Gigawatt data centers, built in America, delivered in months. We're hiring the people who build them. Fluidstack publishes Fluids

  • Graphcore

    Graphcore is a Bristol-origin semiconductor company known for Intelligence Processing Units for machine learning. Public materials cover AI compute hardware and software stacks for

  • Lambda

    Train and scale AI on NVIDIA VR200 NVL 72, GB300 NVL 72, B300, B200, H200, H100, and and more GPUs. Lambda publishes Lambda GPU Cloud as named AI products. Lambda is used for GPU /

  • Modal

    Modal provides high-performance AI infrastructure for inference, training, batch jobs, and sandboxes with fast cold starts and autoscaling, defined in Python. Modal is used for GPU

  • Nebius

    Build and scale faster on the purpose-built AI cloud, engineered from silicon to API. Nebius publishes Nebius AI Cloud and Nebius Token Factory as named AI products. Nebius is used

  • NVIDIA

    NVIDIA sells GPUs, CUDA software and AI enterprise stacks used for training and inference. Public pages cover data-centre, cloud and on-prem AI compute. NVIDIA publishes NVIDIA cuO

  • OVHcloud

    OVHcloud offers European public-cloud AI/GPU services for training and inference with strong data-sovereignty positioning. OVHcloud publishes OVHcloud AI as named AI products. OVHc

  • Runpod

    Run training, inference, and batch workloads on the cloud with Runpod. Runpod publishes Runpod GPU Cloud as named AI products. Runpod is used for GPU / compute platforms work. Runp

  • Scaleway

    Scaleway provides European cloud GPU instances and generative AI APIs for model hosting and inference. Scaleway publishes Scaleway Generative APIs / GPU as named AI products. Scale

  • Vast.ai

    Vast.ai publishes Vast.ai GPU Cloud as named AI products. Vast.ai is used for GPU / compute platforms work. Vast.ai is grouped with GPU / compute platforms suppliers. Public produc

Products

Claimed products appear first. Ranking packs and payment do not change this list.

Related categories

Relevant procurement and assurance guides

Frequently asked questions

What is GPU / compute platforms?

GPU and accelerator capacity for training or inference, not a model product. Jobs: gpu vms; reserved clusters; multi-node training fabric.

What should not be listed as GPU / compute platforms?

Products whose buyer job is inference hosting stacks, training platforms, or generative-AI PaaS. Those belong on their own category page so search queries are not split.

Has AI Trustmark independently assessed every GPU / compute platforms supplier?

No. A category listing is descriptive. Independent assessment is shown only on company or product pages that carry Trustmark evidence.

What are GPU / compute platforms?

GPU and accelerator capacity for training or inference, not a model product. Jobs: gpu vms; reserved clusters; multi-node training fabric.

What model or provider changes should a buyer insist on being told about?

Material change usually includes a new model family, new region, new subprocessor, new write-capable tool, or a change that affects logging, privacy or human oversight. Those changes should trigger evidence refresh rather than a silent release.

How should buyers verify where AI customer data is processed?

Ask for the named processing locations, cloud regions and any subprocessors that see prompts, files or outputs. A directory listing is not evidence of residency. Independent assessment records the locations that were in scope on the assessment date.

Does a TrustMark on one product cover the rest of the company?

No. Independent assessment is scoped to the named organisation and, where relevant, the named product. Category pages list suppliers as a topic label. They do not imply that every listed company has been assessed.

What incident-handling evidence is useful for AI suppliers?

Buyers should see how AI-specific failures are detected, contained and notified — including unsafe outputs, data leakage and unauthorised agent actions. An incident policy that never mentions models, prompts or tools is incomplete for this class of product.