REAM
Collection
Compressed MoE models with a reduced number of experts. See additional models at https://huggingface.co/bknyaz. • 11 items • Updated • 5
Qwen3-235B-A22B-Instruct-2507-REAP
This model is a compressed version of Qwen/Qwen3-235B-A22B-Instruct-2507. It is obtained by reducing the number of experts in each MoE layer from 128 to 96 using the REAP baseline method as described in https://bknyaz.github.io/blog/2026/moe/. The compressed model has 180B params (350GB) instead of 235B (470GB) of the original model, reducing storage and GPU memory requirements by roughly 25%. At the same time, the model retains >=99% of the original model's performance on a variety of benchmarks (see Results section below). Additional efficiency optimization (e.g., quantization) can be added similarly to the original model.
See additional details at Qwen3-30B-A3B-Instruct-2507-REAM.
Results
| Model | IFeval | AIME25 | GSM8K | GPQA-D | HumanEval | LiveCodeBench | AVG |
|---|---|---|---|---|---|---|---|
| Qwen3-235B-A22B-Instruct-2507 | 93.3 | 66.7 | 89.4 | 48.5 | 95.1 | 46.4 | 73.2 |
| Qwen3-235B-A22B-Instruct-2507-REAP | 92.0 | 63.3 | 88.8 | 46.0 | 94.5 | 53.1 | 72.9 |
License
Please refer to the license of the original model Qwen/Qwen3-235B-A22B-Instruct-2507.
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