Ateron/Gemma-4-Dark-Thoughts-V2-31B

Hugging Face
VISIONConcurrent Unit Cost:2Model Size:31BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Aug 13, 2026License:apache-2.0Architecture:Transformer0.0K Open Weights Featherless Exclusive Warm

Ateron/Gemma-4-Dark-Thoughts-V2-31B is a 31 billion parameter language model based on the Gemma-4 architecture, developed by Ateron. This merged model is specifically designed to enhance tool calling capabilities and improve long-context role-play performance, addressing limitations found in its predecessor. It is optimized for creative applications requiring nuanced understanding and interaction within extended conversational scenarios.

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Overview

Ateron/Gemma-4-Dark-Thoughts-V2-31B is a 31 billion parameter model built upon the Gemma-4 architecture, developed by Ateron. This version, V2, focuses on improving upon the original Dark-Thoughts model, specifically addressing issues related to tool calling and maintaining coherence in long-context role-playing scenarios. The development involved a refined recipe with an emphasis on experimental approaches and filtering techniques.

Mergekit Configuration

The model was created using a two-phase mergekit process, leveraging the dare_ties method.

  • Phase 1: Spark involved merging Gemma-4-MeroMero-V2 and Gemma-4-Dark-Scarlett-V2 to ignite creativity.
  • Phase 2: Form polished the model's capabilities by merging Gemma-4-Scotoma-V2 and Dark-Mero-V3.

This intricate merging strategy aimed to enhance specific aspects of the model's performance, particularly in complex interactive tasks.

Key Capabilities

  • Improved Tool Calling: Enhanced ability to integrate and utilize external tools effectively.
  • Long-Context Role-Play: Better performance and coherence in extended conversational and role-playing scenarios.
  • Creative Applications: Designed to support creative text generation and nuanced interactions.

Good For

  • Applications requiring robust tool integration.
  • Complex role-playing and interactive storytelling.
  • Scenarios demanding sustained contextual understanding over long conversations.