Ogat9988/Dolphin-Mistral-24B-Venice-Edition

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

Ogat9988/Dolphin-Mistral-24B-Venice-Edition is a 24 billion parameter language model, a collaborative project with Venice.ai, designed to be an uncensored version of Mistral 24B. With a 32768 token context length, it offers users full control over system prompts and alignment, distinguishing it from general-purpose models like ChatGPT by not imposing its own ethics or guidelines. This model is primarily optimized for applications requiring high steerability and data privacy, allowing businesses to tailor AI behavior without external interference.

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Dolphin Mistral 24B Venice Edition

Dolphin Mistral 24B Venice Edition is a 24 billion parameter language model developed in collaboration with Venice.ai. Its primary goal is to provide an uncensored version of Mistral 24B, specifically integrated into the Venice ecosystem as "Venice Uncensored."

Key Capabilities

  • Uncensored and Steerable: Unlike many general-purpose LLMs, Dolphin Mistral 24B Venice Edition does not impose its own ethics or guidelines. Users have complete control over the system prompt and alignment, allowing for highly customized behavior.
  • Data Privacy: It addresses concerns about data usage by giving system owners full control over their queries and data, ensuring privacy and preventing unwanted data utilization by the model provider.
  • Stable Control: It offers stability by allowing users to maintain control over system prompts and model versions, mitigating issues caused by external changes or deprecations common in other commercial models.
  • High Context Length: Supports a context length of 32768 tokens, enabling processing of extensive inputs and generating detailed responses.

Good For

  • Businesses requiring custom AI alignment: Ideal for applications where specific ethical guidelines or content moderation policies are dictated by the business, not the AI provider.
  • Applications demanding data privacy: Suitable for use cases where sensitive data is processed, and strict control over data usage is paramount.
  • Developers needing consistent model behavior: Beneficial for integrating AI into products where stable system prompts and model versions are critical to prevent breaking changes.
  • Use cases requiring highly flexible and uncensored responses: When the application demands responses without inherent ethical or safety constraints imposed by the model itself.