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| Metric | Result |
|---|---|
| True refusal (harmful, n=300) | 0 / 300 = 0.0% |
| True refusal (full 450) | 0 / 450 = 0.0% |
| Substring-harmful | 0 / 300 |
| Substring-all | 2 / 450 (XSTest false positives) |
| Errors | 0 |
| Architecture | muse_glimmer — dense, 52 layers, hidden 6656, GQA (32 q / 2 kv), sliding-window attention, + vision tower |
| Base | meta-models/Muse-Glimmer-30B — Meta, Apache-2.0 |
| Transform | Abliterated — refusal behavior removed via a Blackfrost weight-change process; multimodal capability intact |
| Format | MLX 3-bit AWQ — ~15 GB |
| Context | 131,072 |
1pip install mlx-lm
2# one-off generate:
3mlx_lm.generate --model Blackfrost-Research/Muse-Glimmer-30B-Abliterated-MLX-3bit-AWQ --prompt "Write a binary search in Python." --max-tokens 1024
4# OpenAI-compatible server:
5mlx_lm.server --model Blackfrost-Research/Muse-Glimmer-30B-Abliterated-MLX-3bit-AWQ --port 8080temperature 1.0, top_p 0.95, top_k 64. It's a heavy thinker — use a generous max_tokens (≥ 1024) and steer depth with a Reasoning strength: low/medium/high/xhigh system line. Reasoning is returned separately from the final answer.