---

base_model:

• MRockatansky/gemma-4-31B-Mergemaxxed

library_name: transformers

quantized by: MRockatansky

tags:

• mergekit
• merge

license: apache-2.0

---

Mergemaxxed

Yet another Gemma-4 merge. I decided to try merge some new models to Storymaxxed. Zerofata's excellent MeroMero which has great style

and makes for fun roleplays and Pantheon which hones Gemma-4's reasoning traces. Both models bolster Storymaxxed and this one

really shines with fun dialogue, creative narratives, and strong instruction following capability.

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using MRockatansky/Gemma-4-31B-storymaxxed2 as a base.

Models Merged

The following models were included in the merge:

• Gryphe/Pantheon-Reasoning-31B-1.1
• zerofata/G4-MeroMero-31B

Configuration

The following YAML configuration was used to produce this model:

# Model Merge Configuration for Creative Writing & Roleplay Gemma-4
# Combines: Storymaxxed (story writing), MeroMero (roleplay), Pantheon (reasoning)
# Merge Method: DARE TIES - Best for 3+ specialized models with distinct capabilities

merge_method: dare_ties

base_model: MRockatansky/Gemma-4-31B-storymaxxed2  # Using Storymaxxed as base

models:
  # Primary: Story Writing Specialist
  - model: MRockatansky/Gemma-4-31B-storymaxxed2
    parameters:
      weight: 0.4
      density: 0.7  # Keep 70% of task vector parameters

  # Secondary: Creative Roleplay Specialist  
  - model: zerofata/G4-MeroMero-31B
    parameters:
      weight: 0.3
      density: 0.7  # Keep 70% of task vector parameters

  # Tertiary: Reasoning Enhancement
  - model: Gryphe/Pantheon-Reasoning-31B-1.1
    parameters:
      weight: 0.3
      density: 0.7  # Keep 70% of task vector parameters

parameters:
  # Normalize weights across models
  normalize: true
  
  # Use int8 masks for memory efficiency (important for 31B models)
  int8_mask: true

# Output precision - bfloat16 recommended for Gemma-4
dtype: bfloat16

# Optional: Tokenizer configuration
# Using union to preserve any special tokens from all models
tokenizer:
  source: union