rbinrs/Dolphin-Mistral-24B-Venice-Edition

VISIONPricing:Input $0.867 / Output $1.61Concurrent Unit Cost:2Model Size:24BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 12, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

Dolphin Mistral 24B Venice Edition is a 24 billion parameter Mistral-based language model developed collaboratively by rbinrs (Dolphin) and Venice.ai, featuring a 32768 token context length. It is specifically fine-tuned to be highly uncensored and steerable, allowing users complete control over system prompts and alignment. This model is designed for general-purpose applications where custom ethical guidelines and data privacy are paramount, contrasting with more restrictive commercial LLMs.

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Overview

Dolphin Mistral 24B Venice Edition is a 24 billion parameter language model, a collaborative effort between Dolphin (rbinrs) and Venice.ai. It is built upon the Mistral architecture and features a 32768 token context length. The primary goal of this model is to provide an uncensored and highly steerable AI, giving users full control over its behavior and alignment through system prompts.

Key Capabilities

  • Uncensored Responses: Designed to follow instructions without ethical, legal, or moral reservations, as defined by the user's system prompt.
  • Full System Prompt Control: Users can define the model's tone, character, and behavioral rules, ensuring responses align precisely with application needs.
  • Data Privacy: Unlike many commercial models, Dolphin Mistral 24B Venice Edition does not impose its own ethics or guidelines, nor does it use user queries for data collection, offering enhanced privacy.
  • General Purpose: Aims to serve as a versatile language model for a wide range of applications, similar to models like ChatGPT or Claude, but with user-defined alignment.

Good For

  • Applications requiring custom alignment: Ideal for businesses or developers who need to integrate AI with specific, non-standard ethical or behavioral guidelines.
  • Use cases demanding uncensored output: Suitable for scenarios where strict content filters of other models are prohibitive.
  • Developers prioritizing data control: Beneficial for those who need assurance that their queries and data will not be used or monitored by the model provider.
  • Integration into the Venice ecosystem: Serves as the default "Venice Uncensored" model on the Venice.ai platform.

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