> ## Documentation Index > Fetch the complete documentation index at: https://documentation.datalab.to/llms.txt > Use this file to discover all available pages before exploring further. # Overview > Run inference on your own infrastructure **Customers can run our models on infrastructure they control with an Enterprise contract.** To get started, please [**fill out this form**](https://www.datalab.to/contact). # **What’s the difference between Open Source and Datalab's paid On-Prem options?** Our free open-source options ([Chandra](https://github.com/datalab-to/chandra), [Marker](https://github.com/datalab-to/marker), and [Surya](https://github.com/datalab-to/surya)) are ideal for research, personal use, and early-stage startups. The model weights are free for research and personal use by anyone. Commercial use is also free if your company is under the threshold on **both** prior-year gross revenue and total funding raised: **\$2M for Chandra** and **\$5M for Marker and Surya**. Above either threshold, you need a commercial license. The open-source license also doesn't cover use by anyone offering a product that competes with Datalab. The exact terms are in each repo's model license. Our paid on-prem options are for teams that need a commercial license to run our models and have one or multiple of the following requirements: * Require data privacy/operate in highly-regulated environments * Extremely high volume * Model training or customization * White-glove support and SLAs Here’s a more detailed breakdown. | | **Free (Open Source)** | **Datalab On-Prem** | | - | - | :- | | **Intended Use** | Research, personal use, startups under \$2M (Chandra) or \$5M (Marker, Surya) in both revenue and funding | Commercial workloads requiring data privacy, easy deployments, and white-glove support | | **Models** | Open source model weights | Access to newer, more accurate models not available in open source (e.g., latest Chandra versions) | | **License** | Apache 2.0 code, modified OpenRAIL-M model weights | Commercial license to use our models on-prem (Marker/Surya/Chandra) without sublicensing. Custom rights as needed. | | **Deployment** | Self-install from OSS repos | Custom deployment topologies and Datalab-assisted rollout options as-needed. For small deployments, we have a Docker image that is simple to use and upgrade. | | **Support** | Community only | Premium support with SLAs | | **Contracting** | None | Custom agreements and security reviews. For POCs and small deployments we offer no-redline agreements to get started, fast. | | **Billing** | Free | Invoice/PO, custom terms. For small deployments we offer credit card checkout. | | **Scale and Performance** | Self-effort | Throughput/latency/accuracy tuning; custom page counts; custom rate limits. For small deployments we offer optimized single-GPU support that is simple to deploy and operate. | For higher page volume & GPU concurrency, fully-airgapped deployments, white glove support, and other custom needs, # **Try before you buy** We have two easy ways for customers to try our models: * Our open-source projects, [Chandra](https://github.com/datalab-to/chandra), [Marker](https://github.com/datalab-to/marker), and [Surya](https://github.com/datalab-to/surya). * Datalab's [Cloud API](https://www.datalab.to). Our container image mimics the cloud-hosted API for a simple transition: * [Cloud API Docs](https://documentation.datalab.to/docs/welcome/api) * [On Prem Container API Docs](./api) ## Next Steps Get the on-prem container up and running in minutes. API reference for the on-prem container image. Try the cloud-hosted API to evaluate before deploying on-prem. Understand pricing for on-prem and cloud plans. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.