Provider Overview
Strengths & Best For
Sesterce is a French GPU cloud offering one of the widest GPU selections in Europe — 26 GPU types including A30, A100, and H100 — across 11 EU regions, making it the broadest European GPU cloud for teams with diverse hardware requirements. On-demand and reserved billing options are available with competitive pricing for AI training, LLM fine-tuning, and inference workloads. A top choice for EU AI teams that need GPU variety and GDPR-compliant European data residency.
- 26 GPU types
- 11 regions
- EU-based infrastructure
- Competitive A30/A100 pricing
Packet AI provides bare-metal L40S and H100 GPU servers with no virtualization overhead and straightforward on-demand billing, making it a cost-effective option for AI inference and training workloads that need dedicated hardware performance. Bare-metal configurations eliminate the latency and overhead of hypervisor layers, delivering consistent GPU throughput for production LLM inference and model deployment. A practical choice for teams that need dedicated GPU hardware without the complexity of managed cloud services.
- Competitive L40S pricing
- Bare metal performance
- No virtualisation overhead
- Simple billing
Live GPU Pricing
Region Coverage
Popular Comparisons
Sesterce — specialist provider
Sesterce is a French GPU cloud offering one of the widest GPU selections in Europe — 26 GPU types including A30, A100, and H100 — across 11 EU regions, making it the broadest European GPU cloud for teams with diverse hardware requirements. On-demand and reserved billing options are available with competitive pricing for AI training, LLM fine-tuning, and inference workloads. A top choice for EU AI teams that need GPU variety and GDPR-compliant European data residency.
Packet AI — bare-metal provider
Packet AI provides bare-metal L40S and H100 GPU servers with no virtualization overhead and straightforward on-demand billing, making it a cost-effective option for AI inference and training workloads that need dedicated hardware performance. Bare-metal configurations eliminate the latency and overhead of hypervisor layers, delivering consistent GPU throughput for production LLM inference and model deployment. A practical choice for teams that need dedicated GPU hardware without the complexity of managed cloud services.
Billing model comparison
Sesterce uses a On-demand, Reserved billing model with a minimum commitment of None. Packet AI uses On-demand billing with a None minimum. Both providers offer flexible billing options — compare the live pricing table above to find the best rate for your specific GPU model and workload duration.
Which workloads each provider suits best
Sesterce is best suited for: EU AI teams, Wide GPU variety needs, Cost-sensitive European workloads. Its key strengths are 26 gpu types, 11 regions, eu-based infrastructure. Packet AI is best suited for: Inference workloads, Cost-sensitive L40S users, Bare metal performance. Its key strengths are competitive l40s pricing, bare metal performance, no virtualisation overhead. Both providers target similar workload profiles — the live pricing table above is the most reliable way to determine which offers better value for your specific GPU model and region requirements.
Support tiers and region coverage
Sesterce offers Standard → Enterprise support across 4 regions (EU-West, EU-Central, US and 1 more). Packet AI offers Standard support across 1 region (US). Sesterce's broader region footprint gives it an advantage for latency-sensitive workloads or teams with data residency requirements in specific geographies.
Provider background: Sesterce vs Packet AI
Sesterce was founded in 2018 and is headquartered in Marseille, France. Packet AI was founded in 2023 and is headquartered in United States. Sesterce has 5 years more operational history than Packet AI, which may matter for teams evaluating provider stability and long-term contract risk. Use the live pricing table above to compare current on-demand and spot rates for specific GPU models, and the region map to verify coverage in your target geography.