Local LLMs
Execute a Large Language Model (LLM) directly within a DaDesktop environment, eliminating the need to transmit prompts to external APIs. The model operates on DaDesktop's GPU infrastructure, ensuring that your prompts, files, and data remain contained within the desktop session. This setup allows you to pay for the desktop resource rather than per token usage.
Reasons to run LLMs locally
- Maintain data privacy: Your prompts, files, and other data remain securely within the DaDesktop environment.
- Avoid per-token fees: Utilize DaDesktop's GPU infrastructure to run the model without incurring API costs for each request.
- Model selection: Choose the specific model you wish to deploy and have full control over its configuration.
- Custom workloads: Execute the model directly from the desktop, integrating it seamlessly with other applications and tools.
AI agents
Deploy agents that leverage local models to complete tasks and interact with various tools.
Coding
Utilize local models to support coding assistance, development workflows, and testing processes.
Research and experimentation
Leverage models for research, in-depth analysis, and experimenting with different models and configurations.
Operational Overview
Select a DaDesktop GPU desktop, load your preferred model, and run it locally. GPU passthrough provides the desktop with full access to a physical GPU, optimized for LLM workloads. You can review available GPUs, specifications, and supported configurations on the GPU page.
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