MergekitCloud/mergekit-52

TEXT GENERATIONPricing:Input $0.37 / Cached $0.074 / Output $0.38Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:8kTool Calling:SupportedPublished:Aug 25, 2026Architecture:Transformer Featherless Exclusive Cold

MergekitCloud/mergekit-52 is an 8 billion parameter language model, merged using the Model Stock method with vicgalle/Humanish-Roleplay-Llama-3.1-8B as its base. This model integrates several Llama 3.1-8B variants, including Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2, ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.3, and Undi95/Llama3-Unholy-8B-OAS. It is specifically designed to combine and enhance the characteristics of its constituent models, likely focusing on nuanced conversational and roleplay capabilities.

Loading preview...

Overview

MergekitCloud/mergekit-52 is an 8 billion parameter language model created through a merge of several pre-trained models using the mergekit tool. The merge process utilized the Model Stock method, as detailed in the paper "Model Stock: A Method for Merging Large Language Models".

Merge Details

This model uses vicgalle/Humanish-Roleplay-Llama-3.1-8B as its base model. It integrates the following Llama 3.1-8B variants:

  • Orenguteng/Llama-3.1-8B-Lexi-Uncensored-V2
  • ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.3
  • Undi95/Llama3-Unholy-8B-OAS

Key Characteristics

The merge configuration specifies int8_mask: true and dtype: float16, indicating an optimization for efficiency while maintaining performance. The selection of base and merged models suggests a focus on enhancing conversational depth, potentially in areas like roleplay or nuanced interaction, by combining models known for such capabilities.

Use Cases

Given the nature of the merged models, mergekit-52 is likely suitable for applications requiring advanced conversational abilities, character-driven interactions, or scenarios where a blend of different model personalities or styles is beneficial. Developers looking for a model with combined strengths from several specialized Llama 3.1-8B derivatives may find this merge particularly useful.