
Snowflake Cortex
Best for Enterprise data teams wanting to run LLMs directly on their secure databases without managing external compute.

Best for Data science teams in highly regulated industries needing reproducible, orchestrated research environments.
Domino Data Lab provides an Enterprise MLOps platform designed to unleash the productivity of data science teams. Functioning as an abstraction layer over your preferred cloud infrastructure or on-premise servers, Domino orchestrates compute resources, manages dependencies, and tracks experiments centrally. By integrating directly with NVIDIA GPUs, it ensures that researchers can access the compute they need instantly without relying on IT ticket requests. It is the platform of choice for highly regulated industries like pharmaceuticals and finance.
| GPU Models | A100, V100, Orchestrated Compute |
| GPU Types | A100, Orchestrated Compute, V100 |
| Headquarters | San Francisco, CA |
| Founded | 2013 |
| Availability | Available Now |
| Website | dominodatalab.com ↗ |
💡 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 →
Domino Data Lab GPU cloud pricing starts from $3.00/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.
Domino Data Lab offers A100, V100, Orchestrated Compute GPU instances. Availability varies by region and configuration. Contact the provider through ComputeStacker for current availability.
Domino Data Lab operates data centers in Global. 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 Domino Data Lab and other matching providers. You'll receive proposals within 24 hours — no commitment required.
Domino Data Lab 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.

Best for Enterprise data teams wanting to run LLMs directly on their secure databases without managing external compute.

Best for Data science teams utilizing Metaflow who want Netflix-scale infrastructure orchestration without managing Kubernetes or AWS Batch directly.

Best for Engineering teams looking to deploy complex, multi-model inference pipelines without managing Kubernetes clusters.