Qwen3.6 27B x Claude Opus 4.x - v2
Benchmarks
Qwen3.6-27B-Claude-Opus-Reasoning-Distill-v2
arc arc/e boolq hswag obkqa piqa wino
mxfp8 0.665,0.831,0.910,0.790,0.456,0.813,0.772
Qwen3.6-27B
arc arc/e boolq hswag obkqa piqa wino
mxfp8 0.647,0.803,0.910,0.773,0.450,0.806,0.742
Provided by @nightmedia. All benchmarks were done in mxfp8 precision
🧬 Datasets:
⚡ Use cases
- Coding
- Creative Writing
- Visual Understanding
- General Purpose
Citations and Contributions
- @unsloth - This qwen3 model was trained 2x faster with Unsloth and Huggingface's TRL library.
- @Qwen - Providing a fantastic, native-multimodal base model
Usage
If you need help setting up and configuring this model please follow the Qwen team's instructions in the original model's README