On-Premise LLMs
Execute Large Language Models within a DaDesktop environment, eliminating the need to transmit prompts to third-party APIs. The model operates on DaDesktop's GPU resources, ensuring that all prompts, documents, and sensitive data remain securely contained within the desktop session. This model allows you to pay for the compute environment rather than incurring costs based on token usage.
Benefits of local LLM execution
- Enhanced data privacy: All prompts, files, and operational data are retained strictly within the DaDesktop environment.
- Elimination of per-token fees: Utilize DaDesktop's GPU infrastructure to run models without paying external API providers on a request-by-request basis.
- Full model control: Select the specific model required for your tasks and manage its configuration parameters directly.
- Integrated workflows: Deploy models directly from the desktop, enabling seamless interaction with other local applications and development tools.
AI agents
Deploy agents that leverage local models to autonomously complete tasks and interact with various tools.
Coding
Leverage local models to enhance coding assistance, streamline development processes, and facilitate testing.
Research and experimentation
Utilize models for in-depth research, data analysis, and the evaluation of various architectural configurations.
Operational mechanics
Select a DaDesktop instance equipped with GPU resources, load your chosen model, and initiate local execution. Through GPU passthrough, the desktop gains direct, full access to physical hardware optimized for LLM workloads. You can review available GPU options, technical specifications, and compatible configurations on the GPU page.
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