3MPER0RR/gemma-4-31b-it-3MPER0RR-abliterated

VISIONPricing:Input $0.48 / Cached $0.1 / Output $1.44Concurrent Unit Cost:2Model Size:31BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 1, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold

3MPER0RR/gemma-4-31b-it-3MPER0RR-abliterated is an experimental 31 billion parameter instruction-tuned language model, based on the Gemma-4 architecture, developed by 3MPER0RR. This model features a 32,768 token context length and represents a modified and abliterated version of the original Gemma-4-31b-it, focusing on research and experimentation. It is designed for exploring the effects of specific modifications on the Gemma-4 base model's performance and behavior.

Loading preview...

Model Overview

3MPER0RR/gemma-4-31b-it-3MPER0RR-abliterated is an experimental 31 billion parameter instruction-tuned language model, derived from the Gemma-4-31b-it architecture. Developed by 3MPER0RR, this model is a modified and "abliterated" version, indicating specific alterations from its original form. It maintains a substantial context length of 32,768 tokens, making it suitable for processing extensive inputs.

Key Characteristics

  • Base Model: Built upon the Gemma-4-31b-it architecture.
  • Parameter Count: Features 31 billion parameters, offering significant capacity for complex language tasks.
  • Context Length: Supports a 32,768 token context window, enabling deep understanding of long-form content.
  • Experimental Nature: This version is explicitly designated for research and experimentation, focusing on understanding the impact of specific modifications.
  • License: Distributed under the Apache 2.0 License.

Use Cases

This model is particularly well-suited for:

  • Research and Development: Ideal for researchers and developers interested in exploring the effects of model modifications and "abliteration" techniques on large language models.
  • Comparative Analysis: Can be used to compare the performance and characteristics of modified Gemma-4 versions against the original or other experimental iterations.
  • Instruction-Following Tasks: As an instruction-tuned model, it can be applied to various tasks requiring adherence to specific prompts and instructions, within an experimental context.

Finetunes
1 models