What are the hardware requirements for WeMM Embedding 9B FP8?

WeMM Embedding 9B FP8 requires approximately 10.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed WeMM Embedding 9B FP8 and how large is it?

WeMM Embedding 9B FP8 is developed by Weidows, 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 WeMM Embedding 9B FP8?

WeMM Embedding 9B FP8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

WeMM Embedding 9B FP8 by Weidows — VRAM 10.4GB

Name: WeMM Embedding 9B FP8
Author: Weidows

WeMM Embedding 9B FP8 is an open-source language model by Weidows. Features: 9b LLM, VRAM: 10.4GB, License: apache-2.0, LLM Explorer Score: 0.28.

Base model:finetune:tencent/we... Base model:tencent/wemm-embedd... Conversational Custom code Embedding Endpoints compatible Fp8 Image-text-to-text Multimodal Quantized Qwen3 5 Region:us Video-text-to-text

Model Card on HF 🤗: https://huggingface.co/Weidows/WeMM-Embedding-9B-FP8

WeMM Embedding 9B FP8 Parameters and Internals

LLM Name	WeMM Embedding 9B FP8
Repository 🤗	https://huggingface.co/Weidows/WeMM-Embedding-9B-FP8
Base Model(s)	WeMM Embedding 9B tencent/WeMM-Embedding-9B
Model Size	9b
Required VRAM	10.4 GB
Updated	2026-09-02
Maintainer	Weidows
Model Type	qwen3_5
Model Files	10.4 GB
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	5.2.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|endoftext\|>
Errors	replace

Rank the WeMM Embedding 9B FP8 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 WeMM Embedding 9B FP8

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 Distilled 9B NPU2	256K / GB	2151	3
Qwen3.5 9B	0K / 19.3 GB	12207758	1799
Ornith 1.0 9B	0K / 18.8 GB	1764324	540
Qwable 9B Claude Fable 5	0K / 18.8 GB	1088	115
Qwythos 9B Claude Mythos 5 1M	0K / 18.8 GB	37427	906
WeMM Embedding 9B	0K / 18.8 GB	2618	105
Qwen3.8 9B Distill	0K / 19.3 GB	5839	148
Negentropy Claude Opus 4.7 9B	0K / 18.8 GB	63	26
Ornith 1.5 9B	0K / 18.9 GB	1324	120
Qwythos 9B V2	0K / 19.3 GB	19208	156

Note: green Score (e.g. "73.2") means that the model is better than Weidows/WeMM-Embedding-9B-FP8.