---
license: apache-2.0
base_model:
  - prism-ml/Bonsai-8B-unpacked
  - Qwen/Qwen3-8B
tags:
  - gguf
  - q1_0
  - 1-bit
  - qwen3
  - bonsai
  - bittensor
  - sn40
language:
  - en
  - hi
  - zh
library_name: llama.cpp
---

# ralph-v2-qwen3-8b-binary-p2A2-step500

A 1-bit (Q1_0 GGUF, 1.0 code bits / 1.125 container bits per weight) Qwen3-8B-architecture model,
the SN40 (Ralph v2) binary-tier crown from round 7.

**License: Apache-2.0** — for the exact file `model.gguf` in this repository (sha256
`05c568169fc180067172cbdd38c1a9f5c249a556ffdef1dacd7172bad40fab58`, chain-pinned revision
`29c525c5c3166df2d62d5e180d09255199f778fe`).

## Lineage and upstream terms to preserve

| component | source | license | what we preserve |
|---|---|---|---|
| binary weights (signs) | [prism-ml/Bonsai-8B-unpacked](https://huggingface.co/prism-ml/Bonsai-8B-unpacked) (PrismML) | Apache-2.0 | attribution / notice |
| architecture, tokenizer, parent behaviour | [Qwen/Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) (Alibaba Cloud) | Apache-2.0 ([LICENSE](https://huggingface.co/Qwen/Qwen3-8B/blob/main/LICENSE)) | attribution / notice |
| container / kernels | llama.cpp GGUF Q1_0 | MIT (tooling; not embedded) | — |

Training data used to fit the per-block scales and norms (no dataset text is embedded in the
weights): prompts drawn from public datasets, with targets generated by Qwen/Qwen3-8B.

| dataset | license | note |
|---|---|---|
| nvidia/OpenMathReasoning | CC-BY-4.0 | attribution required |
| zake7749/OpenScience-Chinese-Reasoning-SFT | CC-BY-4.0 | attribution required |
| glaiveai/reasoning-v1-20m | Apache-2.0 | |
| sarvamai/samvaad-hi-v1 | Apache-2.0 | |
| ricdomolm/mini-coder-trajs-400k | MIT | |

## Method (brief)

Bonsai-8B's 1-bit signs are kept bit-exact; only the 128-element group scales and the RMSNorm
weights were re-fitted by distillation from Qwen3-8B's own generated continuations
(KL(parent‖student) on parent-step tokens, with extra weight on the first tokens of each step and
an unlikelihood penalty on chat-template leak tokens), then exported losslessly to Q1_0.
Selection used a 720-item private pool scored under three observers. Contains no auto_map,
no code, and no dataset text.

## Attribution

- Qwen3-8B © Alibaba Cloud, Apache-2.0.
- Bonsai-8B © PrismML, Apache-2.0.
- OpenMathReasoning © NVIDIA, CC-BY-4.0. OpenScience-Chinese-Reasoning-SFT © zake7749, CC-BY-4.0.