Dolphin 3.0 Llama 3.2 3B Overview

Dolphin 3.0 is an instruct-tuned model from the Dolphin series, developed by Eric Hartford, Ben Gitter, BlouseJury, and Cognitive Computations. This 3.2 billion parameter model is engineered to be a versatile, general-purpose local AI, capable of handling a wide range of tasks including coding, mathematics, agentic operations, and function calling. It distinguishes itself from proprietary models by offering users complete control over the system prompt and alignment, ensuring data privacy and customizable ethical guidelines.

Key Capabilities & Differentiators

General Purpose: Designed for broad applicability, similar to models like ChatGPT, Claude, and Gemini, but with a focus on local deployment and user control.
User Steerability: Users can define the system prompt and alignment, allowing for tailored behavior and ethical guidelines without external imposition.
Data Privacy: Guarantees that user queries and data remain private, as control resides entirely with the system owner.
Consistent Performance: Avoids issues of deprecation or silent changes common with proprietary models, providing a stable foundation for business applications.
Flexible System Prompting: Supports detailed system prompts to set character, mood, and behavioral rules, enabling highly customized interactions.

Ideal Use Cases

Custom AI Applications: Businesses and developers requiring full control over model behavior, alignment, and data handling.
Coding Assistance: Effective for generating and understanding code, particularly when specific language constraints are applied via the system prompt.
Mathematical and Agentic Tasks: Suitable for complex problem-solving and automated workflows where precise control over responses is critical.
Local Deployment: Optimized for scenarios where models need to run locally, ensuring privacy and consistent access.