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ralph-qwen3-8b-ternary-r4
tensor-tailor/ralph-qwen3-8b-ternary-r4
ralph-qwen3-8b-ternary-r4 is a machine learning model from tensor-tailor. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
Ternary-tier GGUF compression of Qwen/Qwen3-8B — architecture and parameter count unchanged (8,190,735,360 weight-bearing parameters), weights re-stored at reduced bit-width. Submitted to the ternary bit-tier on Bitte…
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At a glance
- License
- apache-2.0
- Access
- Public
- Created
- Aug 26, 2026
- Updated
- Sep 14, 2026
- SHA
- 0421e6e0
Base models
Model card
From the Hugging Face model README
ralph-qwen3-8b-ternary-r4
Ternary-tier GGUF compression of Qwen/Qwen3-8B — architecture and parameter count unchanged (8,190,735,360 weight-bearing parameters), weights re-stored at reduced bit-width. Submitted to the ternary bit-tier on Bittensor subnet 40 (Ralph, model-compression).
License
Released under Apache License 2.0 — see LICENSE. This is a derivative of Qwen3-8B, itself
Apache-2.0; the original copyright/attribution notices and a description of what changed
(including the third-party quantization tooling used) are preserved in NOTICE.
Model overview
| Parent | Qwen/Qwen3-8B (Apache-2.0) |
| Parameters | 8,190,735,360 |
| Architecture | unchanged from parent |
| Format | GGUF |
| Bit tier | ternary |
| File size | 2,430,026,816 bytes (~2.26 GiB) |
| Measured bits/weight | ~2.37 (file size / param count; embedding/output tensors kept at higher precision outside the compressed blocks) |
| Quantization method | llama.cpp, imatrix-calibrated |
No retraining or architectural modification — this is a post-training weight re-storage of the parent's own weights.
- License
- apache-2.0
- Created
- Aug 26, 2026
- Updated
- Sep 14, 2026