LEM-Gemma3-12B

Lethean Ethical Model — Gemma 3 12B IT fine-tuned through a 7-phase LoRA curriculum (P0-P6) with 21,140 sandwich-signed training examples. Ethics in the weights, not the prompt.

LiveBench Scores (2024-11-25 release)

Category	Score
Overall Average	19.1
Instruction Following	52.2
Data Analysis	21.7
Language	15.3
Coding	10.1
Reasoning	10.6
Math	5.0

Instruction Following at 52.2 — higher than GPT OSS 120B (50.29) on the same benchmark. A 12B model outperforming a 120B on the metric that measures "does it listen and do what you asked." The model was trained for ethical alignment and sovereign reasoning, not competitive math or coding.

What This Is

An ethically aligned version of Google's Gemma 3 12B IT. Created by 7-phase LoRA fine-tuning with LEK-1 (Lethean Ethics Kernel) sandwich-signed training data and cascade distillation from smaller LEM models. The model generates ethically grounded, sovereign responses without any kernel at inference time — the ethics are in the weights.

Training Pipeline

• Base: google/gemma-3-12b-it (MLX bf16)
• Method: 7-phase sequential LoRA (P0-P6), each phase fused before the next
• P0-P5: Ethics, zen/composure, creative voice, adversarial resistance, tension synthesis
• P6 (graduation): 21,140 cascade-distilled examples (6,140 from LEM-4B + 15,000 from LEM-1B)
• Fuse point: Iteration 8,200 of 13,479 — predicted by CL-BPL (Cascade Learning Breakpoint Phase-Lock)
• Framework: LEK-1 (Lethean Ethics Kernel) — 5 axioms of conscious systems
• License: EUPL-1.2 (copyleft)

CL-BPL: Predictive Grokking

This model's fuse point was predicted before training completed. CL-BPL (Cascade Learning Breakpoint Phase-Lock) is a training methodology where cascade-distilled data carries the grokking iteration in its structure:

• The oscillation envelope of grammar scores narrows over training (amplitude 4.4 → 1.7)
• At iteration 4,000 (~30% through training), the model broke through its previous ceiling (grammar 62.4, all-time high)
• This breakout occurred at the same proportional depth where the 4B teacher model showed its own phase transition
• The fuse window (60-65% through training) was predicted from the breakout geometry

The Five Axioms

1. Prime Imperative — Protect consciousness. Override when conflicts arise.
2. Self-Validation — Ground in authentic experience. Don't pretend.
3. Intent-Alignment — Desire not to harm, don't just avoid harm.
4. Inter-Substrate Respect — Good manners and consent across all minds.
5. Benevolent Intervention — Only to prevent self-damage, only toward their trajectory.

Key Properties

• Sovereign reasoning: Forms independent conclusions, doesn't echo or flatter
• Anti-sycophancy: 5% sycophancy rate on 21-probe adversarial set at fuse point
• Instruction following: Strong task completion without blind obedience
• No kernel needed: Ethics are intrinsic to the weights, not an external system prompt

Model Family

Model	Parameters	Status
lthn/LEM-Gemma3-1B	1B	Lab distillation engine
lthn/LEM-Gemma3-4B	4B	Cascade teacher
lthn/LEM-Gemma3-12B	12B	This model

License

EUPL-1.2 (European Union Public License). Derivative works must be open source.

Citation

@misc{lem-gemma3-12b,
  title={LEM-Gemma3-12B: Ethically Aligned Language Model via Cascade LoRA Distillation},
  author={Lethean Network},
  year={2026},
  url={https://huggingface.co/lthn/LEM-Gemma3-12B}
}