Oracle Cloud
HyperscalerOracle Cloud Infrastructure offers BM.GPU.H100.8 bare-metal nodes and VM.GPU.A10 instances with some of the most aggressive enterprise GPU pricing among hyperscalers. Bare-metal H100 configurations deliver full hardware performance with no virtualization overhead, ideal for large-scale AI training and HPC. Strong Oracle Database integration makes OCI a compelling choice for enterprises running AI alongside data-intensive workloads.
Cheapest On-Demand
$3.46/hr
Cheapest Spot
$1.08/hr
GPU Listings
3
Billing
Pay-as-you-go, Annual Flex
Performance Benchmarks
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Provider Info
Headquarters
Austin, TX
Founded
2016
Regions
us-ashburn-1, us-phoenix-1, eu-frankfurt-1, ap-tokyo-1
Min Commitment
None (pay-as-you-go)
Support
Basic → Premier
Strengths
- ▸Competitive pricing
- ▸Bare-metal GPU options
- ▸Oracle DB integration
- ▸Free tier
Limitations
- ▸Smaller GPU catalog than AWS/GCP/Azure
- ▸Less mature ML tooling and ecosystem integrations
- ▸Support quality inconsistent outside enterprise tiers
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Oracle Cloud GPU pricing overview
Oracle Cloud is a hyperscaler GPU cloud provider headquartered in Austin, TX. Oracle Cloud Infrastructure offers BM.GPU.H100.8 bare-metal nodes and VM.GPU.A10 instances with some of the most aggressive enterprise GPU pricing among hyperscalers. Bare-metal H100 configurations deliver full hardware performance with no virtualization overhead, ideal for large-scale AI training and HPC. Strong Oracle Database integration makes OCI a compelling choice for enterprises running AI alongside data-intensive workloads. Billing is Pay-as-you-go, Annual Flex with a minimum commitment of None (pay-as-you-go). Available regions include us-ashburn-1, us-phoenix-1, eu-frankfurt-1, ap-tokyo-1. On-demand GPU instances can be provisioned in minutes with no upfront cost, making Oracle Cloud suitable for both short-duration experiments and sustained production workloads.
Oracle Cloud vs other GPU providers
Oracle Cloud 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 pricing; Bare-metal GPU options; Oracle DB integration. Use the side-by-side comparison tool above to see Oracle Cloud pricing against any other provider across shared GPU models. For a broader market view, the live GPU prices table shows all 3 Oracle Cloud listings alongside 94+ providers in a single sortable view.
Best use cases for Oracle Cloud
Oracle Cloud is best suited for: Oracle database workloads, Enterprise ML, Cost-sensitive enterprise. Support tiers range from Basic → Premier, making it viable for both individual researchers and enterprise teams with SLA requirements. There are currently 3 active GPU listings on Oracle Cloud, covering H100 80GB, A100 80GB, A10G. 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.
Oracle Cloud billing model and cost structure
Oracle Cloud uses Pay-as-you-go, Annual Flex pricing. On-demand instances are billed per second or per hour depending on the instance type, with no termination fees. Spot (interruptible) instances are available from $1.08/hr — typically 40–70% cheaper than on-demand rates, suitable for fault-tolerant training jobs with checkpointing. 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 Oracle Cloud
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 Oracle Cloud pricing data is collected
Prices shown are sourced from Oracle Cloud'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.
Compare Oracle Cloud with other providers
Side-by-side GPU pricing, spot rates, and available models. View all 102 provider comparisons →
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Launch your first GPU on Oracle Cloud
On-demand from $3.46/hr — 3 GPU configurations available. Pay-as-you-go, Annual Flex billing.