25% of MoE experts pruned (256 → 192) using a creative writing calibration dataset. A lighter prune that preserves more reasoning capability while still significantly reducing model size.
The 50% version (
Timersofc/Qwen3.5-Creative-18B-A3B) is smaller and faster but chain-of-thought reasoning is less stable. This 25% version retains more of the original model's reasoning experts, making it better for:
If you just need short-form creative output and want maximum compression, the 50% version is better value.
All quantizations use an importance matrix generated from the same creative writing calibration dataset used for REAP profiling. This means bit allocation within each tensor is optimized for creative writing — weights that matter most for prose quality get higher precision.
Same as the base model. This is an unofficial community variant, not affiliated with Alibaba or Cerebras.
