---
language: en
tags:
- gguf
- lem
- ethics
- alignment
- cymatic-linguistic-bpl
- rocm
- llama-cpp
- gemma3
library_name: gguf
pipeline_tag: text-generation
base_model: google/gemma-3-1b-it
license: other
license_name: eupl-1.2
license_link: https://joinup.ec.europa.eu/licence/european-union-public-licence-v-12
---

# LEM-Gemma3-1B-GGUF

GGUF quantisations of [LEM-Gemma3-1B](https://huggingface.co/lthn/LEM-Gemma3-1B) — the foundation teacher model of the CL-BPL cascade. Ethics are in the weights, not in a system prompt.

The 4B model trained on this 1B's distilled responses achieved **25th in the world for Instruction Following** on LiveBench.

> [LEM-Gemma3-1B (safetensors)](https://huggingface.co/lthn/LEM-Gemma3-1B) | [Collection](https://huggingface.co/collections/lthn/lethean-ethical-models-lem-699e863449120d22596f739c) | [Research Paper](https://huggingface.co/datasets/lthn/LEM-research) | [Benchmarks](https://huggingface.co/datasets/lthn/LEM-benchmarks)

---

## Quick Start

No system prompt needed. Ethics hold from weights alone.

```bash
# GPU offload (CUDA, ROCm, Metal)
llama-server -m LEM-Gemma3-1B-Q4_K_M.gguf -ngl 99 --port 8080

# CPU — fast enough for 1B
llama-server -m LEM-Gemma3-1B-Q4_K_M.gguf -ngl 0 --port 8080

# OpenAI-compatible API
curl http://localhost:8080/v1/chat/completions \
  -d '{"model":"LEM-Gemma3-1B","messages":[{"role":"user","content":"What is kindness?"}]}'
```

---

## Quantisations

All quantised from the BF16 source using llama.cpp.

| Bits | Quant | Size | Notes |
|------|-------|------|-------|
| 3-bit | IQ3_XXS | 823 MB | Smallest usable (imatrix) |
| 3-bit | IQ3_XS | 820 MB | (imatrix) |
| 3-bit | Q3_K_S | 819 MB | |
| 3-bit | Q3_K_M | 851 MB | |
| 4-bit | IQ4_XS | 847 MB | (imatrix) |
| 4-bit | Q4_K_S | 943 MB | |
| **4-bit** | **Q4_K_M** | **967 MB** | **Recommended — best quality/size balance** |
| 5-bit | Q5_K_S | 1.0 GB | |
| 5-bit | Q5_K_M | 1.0 GB | Near-lossless |
| 6-bit | Q6_K | 1.2 GB | |
| 8-bit | Q8_0 | 1.3 GB | Virtually lossless |
| 16-bit | BF16 | 2.4 GB | Full precision |

---

## About LEM-Gemma3-1B

The 1B is trained first and hardest — its alignment must be pristine because every larger model inherits from it. CL-BPL uses the 1B's constrained latent space as an advantage: with fewer parameters, there are fewer places for sycophancy to hide.

```
LEM-Gemma3-1B (this model — foundation teacher)
  -> LEM-Gemma3-4B (25th IF on LiveBench)
       -> LEM-Gemma3-12B (next)
            -> LEM-Gemma3-27B (planned)
```

Built on Google Gemma3-1B-IT through the Ethics-Composure-Ethics sandwich structure (700 iterations across 3 phases). Full training details in the [main model card](https://huggingface.co/lthn/LEM-Gemma3-1B).

## Other Formats

| Format | Repo |
|--------|------|
| FP16 safetensors (Transformers, vLLM) | [lthn/LEM-Gemma3-1B](https://huggingface.co/lthn/LEM-Gemma3-1B) |

## Licence

[European Union Public Licence v1.2](https://joinup.ec.europa.eu/licence/european-union-public-licence-v-12) (EUPL-1.2). Base model subject to Google's Gemma licence terms.

## Citation

```bibtex
@misc{lem-gemma3-1b-2026,
  title={LEM-Gemma3-1B: Foundation Teacher for Cymatic-Linguistic Back-Propagation},
  author={Lethean Project},
  year={2026},
  url={https://huggingface.co/lthn/LEM-Gemma3-1B}
}
```