A one-shot expert-pruned version of google/gemma-4-26B-A4B-it, produced with the REAP (Router-weighted Expert Activation Pruning) pipeline as a ~4B dense conversion of the original 26B MoE.

Each layer keeps only the K = k = 8 most-salient experts exactly matching top_k_experts. So, every token is routed through all retained experts every time. The sparse routing degenerates into a dense FFN.

	Original	Pruned (this)
Parameters (text MoE)	25.2B	4.39B
Experts per layer	128	8
Active per token	8	8
Weight size (bf16)	~50 GB	8.2 GB
Compression	—	93.75% expert reduction

The dense MLP block already present in each Gemma 4 layer is retained and its output is still summed with the MoE path, as in the original architecture.

Base: google/gemma-4-26B-A4B-it
Method: REAP (Router-weighted Expert Activation Pruning), layerwise error-accumulation calibration

Caveats

It is intended as a research start point (e.g. via logit distillation)
Vision tower and embeddings are unchanged from the original.

License

Apache 2.0, per the original Gemma 4 license. See license_link.

retowyss/gemma-4-26B-A4B-it-REAP2D

Gemma-4-26B-A4B REAP to Dense

Caveats

License

retowyss/
gemma-4-26B-A4B-it-REAP2D