What are the hardware requirements for Qwen3.8 Flash Next Nota NVFP4?

Qwen3.8 Flash Next Nota NVFP4 requires approximately 18.7 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 Flash Next Nota NVFP4 and how large is it?

Qwen3.8 Flash Next Nota NVFP4 is developed by nota-ai, a model with 180b 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 Qwen3.8 Flash Next Nota NVFP4?

Qwen3.8 Flash Next Nota NVFP4 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.8 Flash Next Nota NVFP4 by nota-ai — VRAM 18.7GB

Name: Qwen3.8 Flash Next Nota NVFP4
Author: nota-ai

Qwen3.8 Flash Next Nota NVFP4 is an open-source language model by nota-ai. Features: 180b LLM, VRAM: 18.7GB, License: other, LLM Explorer Score: 0.36.

8-bit Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-flash-... Compressed-tensors Conversational En Endpoints compatible Image-text-to-text Ko Moe Nota Nvfp4 Quantization Qwen4 exp Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/nota-ai/Qwen3.8-Flash-Next-Nota-NVFP4

Qwen3.8 Flash Next Nota NVFP4 Parameters and Internals

LLM Name	Qwen3.8 Flash Next Nota NVFP4
Repository 🤗	https://huggingface.co/nota-ai/Qwen3.8-Flash-Next-Nota-NVFP4
Base Model(s)	Qwen/Qwen3.8-Flash-Next Qwen/Qwen3.8-Flash-Next
Model Size	180b
Required VRAM	18.7 GB
Updated	2026-09-04
Maintainer	nota-ai
Model Type	qwen4_exp
Model Files	0.5 GB: 1-of-265 0.5 GB: 2-of-265 0.3 GB: 3-of-265 0.5 GB: 4-of-265 0.5 GB: 5-of-265 0.3 GB: 6-of-265 0.5 GB: 7-of-265 0.5 GB: 8-of-265 0.3 GB: 9-of-265 0.5 GB: 10-of-265 0.5 GB: 11-of-265 0.3 GB: 12-of-265 0.5 GB: 13-of-265 0.5 GB: 14-of-265 0.3 GB: 15-of-265 0.5 GB: 16-of-265 0.5 GB: 17-of-265 0.3 GB: 18-of-265 0.5 GB: 19-of-265 0.5 GB: 20-of-265 0.3 GB: 21-of-265 0.5 GB: 22-of-265 0.5 GB: 23-of-265 0.3 GB: 24-of-265 0.5 GB: 25-of-265 0.5 GB: 26-of-265 0.3 GB: 27-of-265 0.5 GB: 28-of-265 0.5 GB: 29-of-265 0.3 GB: 30-of-265 0.5 GB: 31-of-265 0.5 GB: 32-of-265 0.3 GB: 33-of-265 0.5 GB: 34-of-265 0.5 GB: 35-of-265 0.3 GB: 36-of-265 0.5 GB: 37-of-265 0.5 GB: 38-of-265 0.3 GB: 39-of-265 0.5 GB: 40-of-265 0.5 GB: 41-of-265 0.3 GB: 42-of-265 0.5 GB: 43-of-265
Supported Languages	en zh ko
Model Architecture	Qwen4ExpForConditionalGeneration
License	other
Transformers Version	5.8.0.dev0

Rank the Qwen3.8 Flash Next Nota NVFP4 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 Qwen3.8 Flash Next Nota NVFP4

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 Flash Next	0K / 129.5 GB	4810	3918
Qwen3.8 Flash Next FP8	0K / 65.7 GB	2219	117
Qwen3.8 Flash Next W4A16	0K / 0.5 GB	6043	22
Qwen3.8 Flash Next FP8	0K / 65.7 GB	185	30
Qwen3.8 Flash Next W4A16	0K / 0.5 GB	541	6
...3.8 Flash Next ABLITERATED FP8	0K / 64.7 GB	254	6
Qwen3.8 Flash Next	0K / 129.5 GB	88	10
...en3.8 Flash Next DERISKED BF16	0K / 129.5 GB	120	2
...Qwen3.8 Flash Next Abliterated	0K / 124.3 GB	64	3
...Next Abliterated FP8 DGX Spark	0K / 61.9 GB	74	2

Note: green Score (e.g. "73.2") means that the model is better than nota-ai/Qwen3.8-Flash-Next-Nota-NVFP4.