D-Wave Leap
Best for Researchers and enterprise teams tackling massive, intractable optimization and logistical ML problems.
from$0.00/ hr★ 8.8/10
Fly.io
Available NowBest for Containerized AI Applications, Low-Latency Edge Inference, Global Web Apps
About Fly.io
Fly.io changed the game for application hosting by pushing Docker containers to the edge, and they are doing the exact same thing for artificial intelligence. By introducing L40S and A100 machines to their global network, developers can now deploy serverless AI inference endpoints right next to their users across the globe.
Deploy Dockerized AI Models Globally
If you are building a consumer-facing AI application where milliseconds matter, Fly.io allows you to spin up a global edge AI GPU deployment in minutes. Their custom networking stack handles all the complex routing, meaning your users in Tokyo hit an Asian GPU, while your users in London hit a European GPU, automatically.
Pros & Cons
Pros
- Deploy dockerized AI models globally with a single CLI command
- Incredible edge-routing technology puts inference nodes millimeters from users
- Highly affordable L40S and A100 compute options
- Extremely active, developer-centric community and documentation
Cons
- Instances are ephemeral or localized, not designed for massive distributed training
- Storage volumes (Fly Volumes) can sometimes be tricky to manage at scale
- H100 multi-node clusters are not available
Ideal Use Cases
AI Inferenceedge-computingmlops
| GPU Models | L40S, A100 |
| GPU Types | A100, L40S |
| Headquarters | Chicago, IL, USA |
| Founded | 2017 |
| Availability | Available Now |
| Website | fly.io ↗ |
$0.40/ hour (starting)—$2.50/ hr (max)
💡 Pricing note: Rates shown are indicative. Final pricing depends on GPU model, reservation type (spot vs. on-demand), contract length, and region. Get an exact quote →
Global (Massively Distributed)
Starting from
$0.40/hr
Up to $2.50/hr
Frequently Asked Questions
Fly.io GPU cloud pricing starts from $0.40/hr depending on GPU type, reservation model (on-demand vs. spot vs. reserved), and region. Use the quote form to get exact pricing for your specific workload.
Fly.io offers L40S, A100 GPU instances. Availability varies by region and configuration. Contact the provider through ComputeStacker for current availability.
Fly.io operates data centers in Asia Pacific, Australia, EU Central, US East, US West. Choosing a region close to your users minimises latency and can help with data residency compliance requirements.
Use the "Get a Quote" button on this page to submit your GPU requirements. ComputeStacker will forward your request to Fly.io and other matching providers. You'll receive proposals within 24 hours — no commitment required.
Fly.io offers high-performance GPU infrastructure suitable for large language model training and fine-tuning workloads. For large-scale distributed training, check the Specs tab for NVLink and InfiniBand interconnect availability.
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