Voltage Park

Voltage Park GPU pricing overview

Voltage Park is a specialist GPU cloud provider headquartered in San Francisco, CA. Voltage Park is a US GPU cloud specializing in large-scale H100 and H200 clusters with competitive on-demand pricing, targeting AI labs and enterprises that need reliable access to flagship NVIDIA hardware for LLM pre-training and distributed AI training. High availability and large cluster configurations make it a strong alternative to CoreWeave for organizations that need multi-node GPU infrastructure without long-term reserved commitments. A top choice for US-based AI teams running large-scale training workloads. Billing is On-demand with a minimum commitment of None. Available regions include US. On-demand GPU instances can be provisioned in minutes with no upfront cost, making Voltage Park suitable for both short-duration experiments and sustained production workloads.

Voltage Park vs other GPU providers

Voltage Park competes with providers including Lambda Labs, CoreWeave, RunPod, Paperspace, Vast.ai, and the major hyperscalers (AWS, Google Cloud, Azure) for GPU compute workloads spanning LLM training, fine-tuning, and inference serving. Key differentiators include: Competitive H100/H200 pricing; High availability; Large cluster sizes. Use the side-by-side comparison tool above to see Voltage Park pricing against any other provider across shared GPU models. For a broader market view, the live GPU prices table shows all 3 Voltage Park listings alongside 94+ providers in a single sortable view.

Best use cases for Voltage Park

Voltage Park is best suited for: Large-scale AI training, H200 workloads, US-based teams. Support tiers range from Standard → Enterprise, making it viable for both individual researchers and enterprise teams with SLA requirements. There are currently 3 active GPU listings on Voltage Park, covering H100 80GB, H200 141GB, A100 80GB. For workloads requiring the highest single-GPU throughput, H100 SXM5 instances with NVLink interconnect deliver the best performance per dollar at scale. For cost-sensitive fine-tuning or inference of models up to 13B parameters, A100 40GB or RTX 4090 instances typically offer the best value.

Voltage Park billing model and cost structure

Voltage Park uses On-demand pricing. On-demand instances are billed per second or per hour depending on the instance type, with no termination fees. Spot pricing is not currently available on this provider — all instances are on-demand. Reserved instance pricing, where available, can reduce costs by 30–60% for predictable long-running workloads. Always compare the effective hourly rate including egress, storage, and networking costs when evaluating total cost of ownership across providers.

Choosing the right GPU on Voltage Park

GPU selection depends on model size, precision, and whether your workload is compute-bound or memory-bandwidth-bound. For LLM training above 30B parameters, H100 80GB SXM5 instances with NVLink are the standard choice — the 3,350 GB/s HBM3 bandwidth and 989 TFLOPS FP16 throughput make them 2–2.5× faster than A100 for transformer workloads. For inference of 7B–13B models in FP16 or BF16, A100 40GB offers the best cost-per-token on most providers. RTX 4090 instances are ideal for fine-tuning, prototyping, and quantized inference (INT4/INT8) of models up to 70B. Read the H100 vs A100 guide or the GPU benchmarks for ML guide for a full breakdown.

How Voltage Park pricing data is collected

Prices shown are sourced from Voltage Park's public pricing API or pricing page and refreshed every 15 minutes. On-demand rates reflect the current list price for a single GPU instance in the cheapest available region. Spot prices, where available, reflect interruptible instance rates at the time of the last snapshot. All prices are in USD per hour. Daily snapshots are retained for 90 days and visualised in the GPU price history charts — useful for identifying seasonal pricing patterns and evaluating whether current rates are above or below the 30-day average.

Evaluating managed LLM inference APIs as an alternative to self-hosted GPU compute? Compare live LLM token prices across OpenAI, Anthropic, Google, Groq, and 14+ other providers. The cheapest GPU cloud guide covers the break-even analysis between self-hosted and managed inference at different request volumes.