AEON-7/Gemma-4-12B-it-AEON-Abliterated-K4-BF16

TEXT GENERATIONConcurrent Unit Cost:1Model Size:12BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Jun 4, 2026License:gemmaArchitecture:Transformer0.0K Featherless Exclusive Cold

AEON-7/Gemma-4-12B-it-AEON-Abliterated-K4-BF16 is a 12 billion parameter bfloat16 model based on Google's Gemma-4-12B-it, developed by AEON-7. This model has undergone a K=4 multi-direction biprojection abliteration process to remove refusal behaviors while preserving core capabilities. It is optimized for fine-tuning and non-Blackwell hardware, offering capability-neutral performance compared to its base model.

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Model Overview

AEON-7/Gemma-4-12B-it-AEON-Abliterated-K4-BF16 is a 12 billion parameter bfloat16 model derived from google/gemma-4-12B-it through a K=4 multi-direction biprojection process. This "abliteration" technique effectively removes refusal behaviors, allowing the model to generate full responses to prompts it would typically decline, while maintaining its original capabilities.

Key Capabilities & Features

  • Refusal-Removed: Generates full responses to prompts that the base model would refuse, often with a brief disclaimer.
  • Capability-Preserving: Benchmarks show performance within ~1 percentage point of the base google/gemma-4-12B-it across MMLU, HumanEval, and IFEval.
  • Optimized for Specific Hardware: This BF16 variant is recommended for fine-tuning tasks or deployment on non-Blackwell hardware.
  • High Concurrency Throughput: Achieves near-linear scaling in aggregate throughput, peaking at ~450-460 tokens/second at c=64 on DGX Spark GB10 with optimized vLLM.
  • Technical Architecture: Features 48 decoder layers, 3840 hidden size, GQA attention, and a 262,144 token vocabulary.

Good for

  • Fine-tuning: Provides a bit-exact weight anchor for further customization.
  • Non-Blackwell Hardware: Ideal for systems not equipped with Blackwell architecture, where its FP8/NVFP4 siblings offer speed advantages.
  • Applications Requiring Unfiltered Responses: Suitable for use cases where the base model's refusal behaviors are undesirable, provided appropriate downstream safety layers are implemented.