What are the hardware requirements for Qwen3.5 REAP 212B A17B?

Qwen3.5 REAP 212B A17B requires approximately 150.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 REAP 212B A17B and how large is it?

Qwen3.5 REAP 212B A17B is developed by OpenMOSE, a model with 397b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Qwen3.5 REAP 212B A17B?

Qwen3.5 REAP 212B A17B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 REAP 212B A17B by OpenMOSE — VRAM 150.8GB

Name: Qwen3.5 REAP 212B A17B
Author: OpenMOSE

Qwen3.5 REAP 212B A17B is an open-source language model by OpenMOSE. Features: 397b LLM, VRAM: 150.8GB, License: apache-2.0, LLM Explorer Score: 0.23.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3.5-397b-a... Qwen3 5 moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/OpenMOSE/Qwen3.5-REAP-212B-A17B

Qwen3.5 REAP 212B A17B Parameters and Internals

LLM Name	Qwen3.5 REAP 212B A17B
Repository 🤗	https://huggingface.co/OpenMOSE/Qwen3.5-REAP-212B-A17B
Base Model(s)	Qwen/Qwen3.5-397B-A17B Qwen/Qwen3.5-397B-A17B
Model Size	397b
Required VRAM	150.8 GB
Updated	2026-07-30
Maintainer	OpenMOSE
Model Type	qwen3_5_moe
Model Files	4.2 GB: 1-of-122 2.3 GB: 2-of-122 4.5 GB: 3-of-122 2.5 GB: 4-of-122 4.5 GB: 5-of-122 2.5 GB: 6-of-122 4.5 GB: 7-of-122 2.3 GB: 8-of-122 4.5 GB: 9-of-122 2.7 GB: 10-of-122 4.5 GB: 11-of-122 2.5 GB: 12-of-122 4.5 GB: 13-of-122 2.5 GB: 14-of-122 4.5 GB: 15-of-122 2.3 GB: 16-of-122 4.5 GB: 17-of-122 2.7 GB: 18-of-122 4.5 GB: 19-of-122 2.5 GB: 20-of-122 4.5 GB: 21-of-122 2.5 GB: 22-of-122 4.5 GB: 23-of-122 2.3 GB: 24-of-122 4.5 GB: 25-of-122 2.7 GB: 26-of-122 4.5 GB: 27-of-122 2.5 GB: 28-of-122 4.5 GB: 29-of-122 2.5 GB: 30-of-122 4.5 GB: 31-of-122 2.5 GB: 32-of-122 4.5 GB: 33-of-122 2.3 GB: 34-of-122 4.5 GB: 35-of-122 2.7 GB: 36-of-122 4.5 GB: 37-of-122 2.5 GB: 38-of-122 4.5 GB: 39-of-122 2.5 GB: 40-of-122 4.5 GB: 41-of-122 2.3 GB: 42-of-122 4.5 GB: 43-of-122
Model Architecture	Qwen3_5MoeForConditionalGeneration
License	apache-2.0
Transformers Version	4.57.0.dev0

Rank the Qwen3.5 REAP 212B A17B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Qwen3.5 REAP 212B A17B

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.5 397B A17B	0K / 369.8 GB	331990	1549
Qwen3.5 397B A17B NVFP4	0K / 251.1 GB	428565	102
Qwen3.5 397B A17B NVFP4 V2	0K / 243.5 GB	23781	5
Ornith 1.0 397B FP8	0K / 147.7 GB	597119	183
Ornith 1.0 397B	0K / 288.5 GB	251974	261
XYZ Aquila Pro	0K / 225 GB	1805	375
Qwen3.5 397B A17B	0K / 369.8 GB	53	13
Qwen3.5 397B A17B FP8	0K / 184.9 GB	825515	182
Ornith 1.5 397B	0K / 279.9 GB	672	66
Ornith 1.5 397B NVFP4	0K / 237.9 GB	2533	15

Note: green Score (e.g. "73.2") means that the model is better than OpenMOSE/Qwen3.5-REAP-212B-A17B.