Coming soon …

 SquidNet Features coming in 2018:

  • Microsoft Azure Cloud ( Ready!! ): Deploy SquidNet completely inside Azure’s Cloud Services
  • Render Bridge (March): Share render farm resources with other SquidNet render farms
  • Dashboard (March): Cloud applet for job submissions. Alternate option for Cloud User Interface
  • Google Cloud (Late April): Full support for all Google Cloud Services
  • Amazon AWS (June): Complete integration with AWS Services

We’re looking for development partners !!

  • In-application plugin developers for Maya, 3DSMAX, Modo, Cinema4D, Houdini , KeyShot and Blender.
  • V-Ray plugin developers with a deep understanding of V-Ray’s rendering pipeline.
  • Beta testers for Azure, AWS and Google Cloud Services workflows.
  • Educational institutions to help us beta test our instructor/student workflow.
  • Deadline Render Farm Manager expert to help us develop our new cloud/remote SquidNet-to-Deadline rendering interface.
  • Machine Learning Scientist with a deep understanding of CPU/GPU ML implementations with distributed computer networks.
  • Free licensing will be provided to all development partners.
  • If interested, please send us an email.

About SquidNet

 Distributed CPU/GPU Rendering

SquidNet is a network render farm manager that supports both cloud and local CPU/GPU rendering. Cloud (outside the local farm) rendering involves submitting jobs remotely via SquidNet’s Cloud User Interface (CUI). Local farm rendering involves submitting jobs inside the local render farm network using SquidNet’s Local User Interface (LUI). Built-in support for Intel/AMD and Nvidia (CUDA)/AMD (OpenCL).

 Cloud Rendering

SquidNet’s cloud rendering workflow allows for direct submission of CPU/GPU jobs from outside the local render farm network. Job submissions can be submitted from a desktop application or from a scriptable command line interface. All communications between remote and local connection are securely protected with OpenSSL AES 256 bit encryption.

 Local Rendering

SquidNet’s local rendering workflow allows for direct submission of CPU/GPU render jobs to a local render farm. Jobs can be submitted using the local job submission interface or from a scriptable command line interface. Standard job management operations (suspend, resume, cancel, etc…) are available from both the GUI and command line interfaces.

 Distributed Computing

SquidNet’s distributed computing workflow can be customized to distribute process-intensive tasks across any number of networked servers. Custom task submission templates can be created to handle any set of application processing parameters. Any application that supports an API/SDK or command-line interface can be integrated into SquidNet’s workflow engine. For additional information on how to integrate your application, send us an email.

 Lease Your Render Farm

With SquidNet’s cloud rendering interface you can lease your idle render farm time to artists and animators outside of your local studio. Use the application licenses already on your local farm to let remote users take advantage of the applications that you already support. Send us an email for more information.

 Amazon Web Services

SquidNet provides the internal hooks to connect to Amazon’s web services. The node management interface between local bare-metal render nodes and Amazon instances is seamlessly integrated into the rendering pipeline. Complete integration is on our future road map. If interested in becoming a development partner, just send us an email.

 Microsoft Azure Cloud

SquidNet is completely integrated into Microsoft’s Azure cloud service. All features available in a local bare-metal render farm are available in the Azure cloud. If interested in becoming a development partner, just send us an email.

 Google Cloud Services

SquidNet provides the internal hooks to connect to Google’s web services. Each Google instance can be used as a local or cloud-based rendering node. Complete integration is on our future road map. If interested in becoming a development partner, just send us an email.

 Machine Learning

SquidNet’s GPU interface provides an ideal candidate for machine learning distributed operations. The front-end local and cloud-based user interfaces provide all the user input data to the back-end GPU processing nodes. When processing is completed, SquidNet bundles up the output content and downloads it to the user’s desktop automatically. Send us an email if you’re interested in becoming a development partner for our machine learning interface design.

 Extensible Interface

SquidNet’s extensible interface can support any compute-intensive task that can be distributed across hundreds of parallel processing nodes. These tasks can include: CPU/GPU animation rendering, virtual reality scene processing, data mining, analytical processing and scientific experimentation. Custom job templates provide users with the flexibility to manage their custom applications across their computer network. Support for any application that provides an sdk/api or command line interface.

 Cross Platform

Support for Windows (7/8/10), Mac OS (Sierra, etc…) and Linux (Ubuntu, Red Hat, Fedora, etc…) Operating Systems. Within each operating system, all graphical user and command line interfaces are identical.  For each platform, there’s just a single installer for the back-end server and a single installer for the front-end Cloud Interface. See download section.

Features That Matter

Local Render Farm Management

Cloud Render Farm Service Management

Complete Render Farm Service Solution

Cloud-based Rendering

SquidNet’s cloud rendering solution includes a desktop GUI application. The CUI provides the interfaces for job submission, uploading image content, downloading rendered images, monitoring activity and job/usage report generation. It’s also the main gateway to SquidNet’s Cloud Command Line interface (CCL). The CUI is available for Windows, Mac OS and Linux operating systems.

Job Management Interface

SquidNet’s cloud job queuing system provides all the tools necessary to manage job submitted from outside the local render farm. Within the farm, all cloud-based jobs and local-based jobs reside within the same job queuing system. Internally, SquidNet doesn’t differentiate between cloud and local job submissions.

Studio Management Interface

SquidNet’s cloud rendering solution includes a sophisticated studio and user management system. Studio accounts are configured to include one or more user accounts, render pools, render nodes, rendering applications, available render credits and more. SquidNet’s proprietary Processor Performance Index (PPI) render credit usage system ensures that all users consume the exact same number of render credits regardless of the rendering horsepower of the rendering node.

Flexible interface

SquidNet’s extensible interface allows for rapid addition of special workflows. Basically, any rendering application that provides a command line interface or application programming interface (API) and be integrated into SquidNet’s workflow. Management of SquidNet workflows can be done using the following interfaces:

  • Local farm command line interface

  • Local JScript/JSON interface

  • SQL database queries

  • Remote (cloud) command line interface

  • Remote (cloud) JScript/JSON interface.

Download Latest

FAQ – Frequently Asked Questions

No. SquidNet 2.x licenses will no longer be valid with the new 3.x release. If you upgrade your version to 3.x, you’ll be provided with a new LOCAL RENDER FARM license.

SquidNet’s licensing models are as follows:

  • Local license:
    • Good for all versions and future updates
    • Unlimited jobs and local users (RenderFarm account)
    • Command line interface and tools
    • SQL Database access
    • Based on number of local render nodes. Renewed annually
  • Cloud license:
    • Includes local license
    • Unlimited studio and user accounts
    • Remote command line interface and tools
    • Based on number of local render nodes. Renewed annually

The cloud interface provides the following types of reports:

  • Per-job render reports
  • Job error email notifications
  • Daily, weekly and monthly studio render reports
  • Periodic farm status render reports
  • Searchable SQL database (via cloud user interface )


You may have an unlimited number of studio accounts and users with the cloud interface. Each studio account provides an interface for admins to create an unlimited number of render accounts.

Technical support is provided by email, phone, Skype and remote desktop connections (AnyDesk, RDP, Teamviewer, etc…).

Free online training is provided upon license purchase. Typical training sessions are as follows:

  • Render Farm Installation (1 hour): Includes installation and setup of master, client and slave render nodes.
  • Local interface (1 hour): Includes job submission, troubleshooting and monitoring of farm activity.
  • Cloud Interface(2 hours): Includes cloud interface, studio and user account setup, render credit setup and monitoring of farm activity.

Please email us to schedule your training session.

SquidNet runs as a background service (daemon on Linux and Mac OS). This service runs at all times and is persistent between host restarts. The main SquidNet GUI connects to the service via direct inter-process communications (IPC – TCP/IP). Service prerequisites are as follows:

  • Windows (Vista, 7, 10, etc…):
    • Full Administrative privileges.
    • Network access privileges
    • Access credentials provided during installation phase
  • Mac OS and Linux:
    • Runs under system root account
    • Network access privileges

Render farms require centralized storage of render content. Farm render nodes access (render) the project content stored on the storage device. Upon render completion, the images are typically written to the same storage device.

Any network accessible storage (NAS) device will suffice. However, use of Windows (non-server) mapped drives are not recommended because Microsoft limits the number of concurrent network connections.

SquidNet uses render credits to determine the amount of rendering resources used by a specific job. Render credit consumption is base on the the PPI (Processor Performance Index) of the rendering node. Higher performing render nodes consume render credits at a higher rate than lower performing render nodes. However, in the end, the overall cost of rendering each frame is the same.

Job profiles are created from application templates and contain the rendering instructions and parameters for a render job. Both the local and cloud interfaces allow job profiles to be created, edited, submitted and saved. Each profile can be re-opened, edited and resubmitted to the render farm.

To obtain an evaluation license just send us an email with a short description of your requirements. Evaluation licenses are good for 15 days but can be extended upon request.

SquidNet supports the following rendering applications:

  • Autodesk Maya
  • Autodesk 3DSMAX
  • Maxon Cinema 4D
  • Blender
  • The Foundry Modo
  • Newtek Lightwave
  • Adobe After Effects
  • The Foundry Nuke
  • Maxwell Render
  • V-Ray Standalone
  • Redshift Standalone
  • more…

SquidNet can support any application that provides an API/SDK or command line interface.

Yes. A 20% license discount is provided for educational institutions.

Reseller agreements can be arranged. Please send us an email for additional information.

For feature requests and recommendations, please send us an email.

Try SquidNet for Free !

Request your free 15-day evaluation license:

Your evaluation license includes:

  • 15-day full feature license
  • Access to both cloud and local rendering interfaces
  • Unlimited jobs and user accounts
  • 1 Hour setup, configuration and training.
  • Support via email or Skype

For further assistance or questions on evaluation licenses, please send us an email.

Pricing and Licensing

License purchasing instructions:

Instruction for purchasing SquidNet licenses are as follows:

  1. Select licensing model that best fits your needs.
  2. Order online thru PayPal by pressing “Order Now” button.
  3. Get us your render farm’s hardware keys by following these instructions.
  4. Once your online payment has been received, you’ll be sent an email with your unique license and installation instructions.
  • For further assistance or questions on evaluation licenses, please send us an email.


  • 2 Render Nodes
  • 3 CPU/GPU Jobs


$5000Yearly (per node)
  • Unlimited Render Nodes
  • Unlimited CPU/GPU Jobs
  • Single Studio Account
  • Unlimited User Accounts
  • SQL Database Access
  • Cloud User Interface
  • Web Interface
  • Training & Support


  • Unlimited Render Nodes
  • Unlimited CPU/GPU Jobs
  • Single Studio Account
  • Unlimited User Accounts
  • SQL Database Access
  • Cloud User Interface
  • Web Interface
  • Training & Support


12500Yearly (per node)
  • Unlimited Render Nodes
  • Unlimited CPU/GPU Jobs
  • Unlimited Studio Accounts
  • Unlimited User Accounts
  • SQL Database Access
  • Cloud User Interface
  • Web Interface
  • Studio Interface
  • Lease Interface
  • Training & Support
  • The Free License is automatically included with the default installation of SquidNet.

  • License prices listed are per node and renewed annually.

  • A single node license covers either a master, client or slave node.

  • A “Single Studio Account” refers to the local “RenderFarm” account.

  • Training (typically 1 hour) and support (Email, phone, Skype, etc…) provided as needed.

  • Discounts available for educational institutions.

  • Reseller discounts are available (for inquiries, send us an email).

Get In Touch With Us

Please send us an email if  you have any questions on the following (response usually within 24 hrs):

  • Evaluation License

  • Support

  • Pricing

  • Development Partnership

  • Feature Request

  • Reseller Information

  • FeedBack

Reach out to us on Skype.

Skype Id: rmacyn

Latest Releases

Render Farm: v3.08

Cloud User Interface: v3.76

Release Date: Feb 12, 2018

Release Notes
Render Farm
Cloud Interface
Render Farm
Cloud Interface
Render Farm
Cloud Interface