Local LLMs
Execute a Large Language Model (LLM) within a DaDesktop environment rather than routing your prompts to an external API. By leveraging DaDesktop's GPU infrastructure to run the model, you ensure that your prompts, files, and other sensitive data remain securely contained within the desktop. This approach shifts the cost model from per-token API fees to a flat desktop rental.
Why run LLMs locally
- Preserve data privacy: Your prompts, files, and other data are kept entirely within the DaDesktop environment, preventing external exposure.
- Eliminate variable costs: Utilize DaDesktop's GPU infrastructure to run models without incurring per-request API charges.
- Customize your model: Select the specific model you require and retain full control over its configuration parameters.
- Integrate custom workloads: Deploy the model directly from the desktop, allowing it to operate seamlessly alongside other applications and tools.
AI agents
Deploy autonomous agents that leverage local models to execute tasks and interact with various tools.
Coding
Leverage local models to support coding assistance, software development, and quality testing.
Research and experimentation
Utilize models for in-depth research, data analysis, and iterative testing of different configurations.
How it works
Select a GPU-enabled DaDesktop, load your preferred model, and initiate local execution. Through GPU passthrough, the desktop gains direct, full access to physical GPU resources, optimized for LLM workloads. You can review available GPUs, technical specifications, and supported configurations on the GPU page.
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