REAP-pruned & quantized Qwen3.5 / 3.6 / Coder variants. • 15 items • Updated
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Qwen3.5-264B
REAP-pruned Qwen/Qwen3.5-397B-A17B.
At a glance
| Base model | Qwen/Qwen3.5-397B-A17B |
| Format | BF16 |
| Total params | 264B |
| Active / token | — |
| Experts / layer | 336 |
| Layers | 60 |
| Hidden size | 4096 |
| Context | 262,144 |
| On-disk size | 527 GB |
Which variant should I pick?
| Variant | Format | Link |
|---|---|---|
Qwen3.5-264B (this) |
BF16 | link |
Qwen3.5-264B-FP8 |
FP8 | link |
Qwen3.5-264B-W4A16 |
W4A16 | link |
Qwen3.5-28B |
BF16 | link |
Qwen3.5-35B-EXL3-4bpw |
EXL3-4bpw | link |
Qwen3.5-76B |
BF16 | link |
Qwen3.5-76B-GGUF |
GGUF | link |
Qwen3.5-88B |
BF16 | link |
Qwen3.5-99B |
BF16 | link |
Qwen3.5-99B-GGUF |
GGUF | link |
- Repository:
0xSero/Qwen3.5-264B - Base model:
Qwen/Qwen3.5-397B-A17B - Artifact kind:
pruned - Compression ratio:
34% - Prune metric:
reap
Details
- Maintainer:
0xSero - Organization:
Sybil Solutions - Project:
REAP PR17 - Hub owner:
0xSero - Summary: BF16 REAP-pruned Qwen3.5-397B-A17B with 176 of 512 experts removed per MoE layer, retaining 336 experts per layer, for an estimated 264B total parameters.
Provenance
- Observer state:
/home/ubuntu/qwen397-full/observer-calibv1/qwen397-pr17-calibv1-23k-16k-observer-state.raw.pt - Detail state:
/home/ubuntu/qwen397-full/observer-calibv1/qwen397-pr17-calibv1-23k-16k-detail-state.raw.pt
Benchmarks
No benchmark summary was found.
Custom Stress
No custom stress summary was found.
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("0xSero/Qwen3.5-264B", trust_remote_code=True)
tokenizer = AutoTokenizer.from_pretrained("0xSero/Qwen3.5-264B", trust_remote_code=True)
License & citation
License inherited from the base model.
@misc{lasby2025reap,
title = {REAP the Experts: Why Pruning Prevails for One-Shot MoE Compression},
author = {Mike Lasby and Ivan Lazarevich and Nish Sinnadurai and Sean Lie and Yani Ioannou and Vithursan Thangarasa},
year = {2025}, eprint = {2510.13999}, archivePrefix = {arXiv}
}
Sponsors
Made possible by NVIDIA · TNG Technology · Lambda · Prime Intellect · Hot Aisle.
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Model size
263B params
Tensor type
BF16
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