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library_name: transformers
tags:
- compression
- expert-merging
- moe
- code
license: apache-2.0
base_model:
- Qwen/Qwen3-Coder-Next
---
arXiv: [REAM: Merging Improves Pruning of Experts in LLMs](https://arxiv.org/abs/2604.04356)
# Qwen3-Coder-Next-REAM
This model is a compressed version of [Qwen/Qwen3-Coder-Next](https://huggingface.co/Qwen/Qwen3-Coder-Next).
It is obtained by reducing the number of experts in each MoE layer from 512 to 384.
This reduction is achieved by the REAM method described in https://bknyaz.github.io/blog/2026/moe/.
**Compared to other models obtained in this collection, more code data is used in the calibration data during pruning/merging
to better preserve original's model coding abilities. Specifically, the ratio between c4, math and coding data (see https://bknyaz.github.io/blog/2026/moe/) is 0.0, 0.3, 0.7.
The calibration data used here is the same as in [Qwen3-Coder-Next-REAP](https://huggingface.co/SamsungSAILMontreal/Qwen3-Coder-Next-REAP).
Compared to other REAM models, here we used C=32 (number of experts in groups) instead of C=16, which we found to work better.**
The compressed model has 60B params (120GB) instead of 80B (160GB) of the original model,
reducing storage and GPU memory requirements by roughly 25%. At the same time,
the model retains 100% (or very close) 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](https://huggingface.co/SamsungSAILMontreal/Qwen3-30B-A3B-Instruct-2507-REAM).
### Results
| Model | IFeval | AIME25 | GSM8K | GPQA-D | HumanEval | LiveCodeBench | AVG |
|--------------------------|--------|--------|-------|--------|-----------|---------------|-------|
| Qwen3-Coder-Next | 89.6 | 80.0 | 85.4 | 42.4 | 92.7 | 47.5 | 72.9 |
| Qwen3-Coder-Next-REAM | 89.3 | 80.0 | 85.3 | 40.4 | 94.5 | 48.0 | 72.9 |
## License
Please refer to the license of the original model [Qwen/Qwen3-Coder-Next](https://huggingface.co/Qwen/Qwen3-Coder-Next). |