qudata.ai provides direct GPU rental and hosting for H100, A100, RTX 4090, H200, L40S, RTX A6000, A10, B200 and other accelerators. Its platform supports dedicated infrastructure with Tier III, Tier IV and PCI DSS coverage.
qudata.ai is a direct operator with a broad GPU lineup spanning current-generation NVIDIA capacity. Running its own network, it suits teams moving from experimentation into sustained production or those that need range across training, inference and fine-tuning without managing separate provider accounts.
The tradeoff: procurement is configuration-dependent and may require a quote process rather than instant checkout. Best fit for buyers with a clear workload plan.
Best for: Buyers who want a direct relationship with the operator that owns the metal. Not for: Teams prioritising a marketplace's breadth of third-party supply.
Confidence: HighEvidence reviewed: 8 checks
Confirmed
Direct operator classification
qudata.ai controls GPU infrastructure and sells access directly. Not a marketplace or hyperscaler resale offer.
REVIEWS
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qudata.ai is classified as a direct operator. Buyers who want a direct relationship with the operator that owns the metal. Teams prioritising a marketplace's breadth of third-party supply.
What GPU models does qudata.ai offer?
qudata.ai lists H200, P100, A40 and 15 more across its published capacity.
How much does qudata.ai charge for GPU compute?
Published indicative rates span Hourly rates at $0.20 – $7.00 /hr, Monthly rates at $135 – $1,687 /mo. Final cluster pricing depends on commit length, storage and networking.
Is qudata.ai's viabandwidth listing verified?
Not yet. This profile is compiled by viabandwidth from public sources. qudata.ai has not claimed it.
OVERVIEW
Company overview
Operator class
Direct operator
GPU models tracked
H200, P100, A40 and 15 more
Services
GPU compute, Bare metal
CAPACITY
GPU lineup by use case
Tracked GPU SKUs grouped by the workload they fit best.
Training
For multi-node runs where interconnect and cluster availability decide the outcome.
H200
QuoteClaim to publish
VRAM 141 GBClass Hopper
Best for Large-scale training where memory bandwidth decides the outcome.
A100
QuoteClaim to publish
VRAM 80 GBClass SXM
Best for Mature training stacks that value known performance and broad tooling support.
MI300X
QuoteClaim to publish
VRAM 192 GBClass AMD
Best for Training and inference for teams evaluating the AMD ecosystem.
H100
QuoteClaim to publish
VRAM 80 GBClass SXM
Best for Serious model training where time-to-result outweighs hourly cost.
Inference
For predictable production serving, latency targets and steady utilisation.
P100
QuoteClaim to publish
Best for P100 workloads.
P40
QuoteClaim to publish
Best for P40 workloads.
RTX3090
QuoteClaim to publish
Best for RTX3090 workloads.
T4
QuoteClaim to publish
VRAM 16 GBClass Turing
Best for Cost-optimised inference for smaller models with predictable load.
Fine-tuning
For smaller adaptation jobs, evaluation loops and budget-controlled development.
A40
QuoteClaim to publish
VRAM 48 GBClass Ampere
Best for LoRA fine-tuning, evaluation and teams watching spend closely.
RTXA6000
QuoteClaim to publish
VRAM 48 GBClass Ampere
Best for Development and fine-tuning with 48 GB of memory at workstation pricing.
COMMERCIALS
Pricing
Indicative published rates. Final cluster pricing depends on commit length, storage, networking and capacity.
Hourly rates
$0.20 – $7.00 /hr
Monthly rates
$135 – $1,687 /mo
Across 16 published SKUs spanning H200, P100, A40, P40.
COMPARE
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Profile pages, buyer guides and model explainers stay open. Vendor packages cover what shows on this profile. Verification stays independent and is never for sale.