Local LLMs
Execute an LLM within a DaDesktop environment instead of routing prompts to an external API. While the model operates on DaDesktop’s GPU infrastructure, your prompts, files, and data remain contained within the desktop instance. This approach allows you to pay for the dedicated desktop resource rather than incurring per-token costs.
Benefits of Local LLM Execution
- Enhanced Data Privacy: Ensure that prompts, files, and all related data are kept secure within the DaDesktop environment.
- Cost Predictability: Utilize DaDesktop’s GPU infrastructure to run models without the financial burden of per-request API fees.
- Model Autonomy: Select and configure the specific models you wish to deploy, giving you full control over the setup.
- Integrated Workloads: Run models directly from the desktop, seamlessly interacting with other applications and tools.
AI Agents
Deploy agents that leverage local models to execute tasks and interact with various tools.
Coding
Utilize local models to assist with coding, development workflows, and testing processes.
Research and Experimentation
Conduct research and analysis by testing different models and configurations to optimize performance.
Operational Workflow
Select a DaDesktop GPU instance, load your chosen model, and run it locally. Thanks to GPU passthrough, the desktop gains full access to physical GPU resources, optimizing it for LLM workloads. You can review available GPUs, technical specifications, and supported configurations on the GPU page.
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