What are the hardware requirements for Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2?

Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 requires approximately 10.9 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 and how large is it?

Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 is developed by goldhub, a model with 9b 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 Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2?

Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 by goldhub — VRAM 10.9GB

Name: Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2
Author: goldhub

Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 is an open-source language model by goldhub. Features: 9b LLM, VRAM: 10.9GB, License: apache-2.0, LLM Explorer Score: 0.29.

4-bit 9b Auto-round Base model:jackrong/qwopus3.5-... Base model:quantized:jackrong/... Conversational El En He Image-text-to-text Mtp Quantized Qwen Qwen3.5 Qwen3 5 Qwopus Region:us Ru Safetensors Sharded Tensorflow Uk Vision W4a16

Model Card on HF 🤗: https://huggingface.co/goldhub/Qwopus3.5-9B-v3-BF16-W4A16-G32-AutoRound-v2

Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 Parameters and Internals

LLM Name	Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2
Repository 🤗	https://huggingface.co/goldhub/Qwopus3.5-9B-v3-BF16-W4A16-G32-AutoRound-v2
Model Name	unsloth/Qwen3.5-9B
Base Model(s)	Jackrong/Qwopus3.5-9B-v3 Jackrong/Qwopus3.5-9B-v3
Model Size	9b
Required VRAM	10.9 GB
Updated	2026-10-31
Maintainer	goldhub
Model Type	qwen3_5
Model Files	1.1 GB: 1-of-10 1.1 GB: 2-of-10 1.1 GB: 3-of-10 1.1 GB: 4-of-10 1.1 GB: 5-of-10 1.1 GB: 6-of-10 0.3 GB: 7-of-10 2.0 GB: 8-of-10 0.0 GB: 9-of-10 2.0 GB: 10-of-10 0.5 GB
Supported Languages	en ru uk el he
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.14.1
Tokenizer Class	TokenizersBackend
Padding Token	<\|vision_pad\|>
Errors	replace

Rank the Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2 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 Qwopus3.5 9B V3 BF16 W4A16 G32 AutoRound V2

Best Alternatives	Context / RAM	Downloads	Likes
HYZ 01 9B	256K / 18.8 GB	102	1
Clef Flash	0K / 18.8 GB	36817	853
Qwen3.5 9B	0K / 19.3 GB	12207758	1799
Qwable 9B Claude Fable 5	0K / 18.8 GB	1088	115
Ornith 1.0 9B	0K / 18.8 GB	807732	565
MiMo V2.6 Distill Qwen 9B	0K / 18.8 GB	5705	429
Qwythos 9B Claude Mythos 5 1M	0K / 18.8 GB	37427	906
Elephant 1	0K / 18.8 GB	1344	75
Flux 3 Image Klein Pup	0K / 18.8 GB	6948	54
LensVLM 9B	0K / 18.8 GB	1840	258

Note: green Score (e.g. "73.2") means that the model is better than goldhub/Qwopus3.5-9B-v3-BF16-W4A16-G32-AutoRound-v2.