Instructions on how to use the server with 4x GTX 1080 and Windows® Server 2016. Step-by-step guide from the moment of choosing the GPU environment to the moment of direct connection to the server.
01 / ANALYST READ
Our read
LeaderGPU is currently under verification. Profile data reflects publicly available information and is subject to change as operator verification completes.
Check back once verification is complete for a more detailed read.
Confidence: LowEvidence reviewed: 1 checks
02 / OVERVIEW
Company overview
Operator class
Pending verification
GPU models tracked
RTX4090, H200, P100 and 12 more
Services
GPU compute, Bare metal
03 / 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.
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.
RTX4090
QuoteClaim to publish
Best for RTX4090 workloads.
P100
QuoteClaim to publish
Best for P100 workloads.
RTX6000
QuoteClaim to publish
Best for RTX6000 workloads.
RTX5090
QuoteClaim to publish
Best for RTX5090 workloads.
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.
04 / TRUST
Verification
Evidence that there's a real operator behind the offer.
Indicator
Verification in progress
Operator classification and network checks are being reviewed. Profile reflects publicly available information.
05 / COMMERCIALS
Pricing
Indicative published rates. Final cluster pricing depends on commit length, storage, networking, and capacity.
Monthly rates
$199 – $6,320 /mo
Across 13 published SKUs spanning RTX4090, H200, P100, RTX6000.
07 / NEXT
Talk to LeaderGPU
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leadergpu.com
Pricing pages, quote forms, and sales routes live on the provider’s own site.
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.