What are the hardware requirements for Qwen3.8 Flash Next 4bit?

Qwen3.8 Flash Next 4bit requires approximately 111.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 Flash Next 4bit and how large is it?

Qwen3.8 Flash Next 4bit is developed by mlx-community, a model with 177.4b 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 4bit?

Qwen3.8 Flash Next 4bit 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 4bit by mlx-community — VRAM 111.2GB

Name: Qwen3.8 Flash Next 4bit
Author: mlx-community

Qwen3.8 Flash Next 4bit is an open-source language model by mlx-community. Features: 177.4b LLM, VRAM: 111.2GB, Quantized, LLM Explorer Score: 0.28.

4-bit 4bit Base model:quantized:qwen/qwen... Base model:qwen/qwen3.8-flash-... Conversational En Image-text-to-text Mlx Quantized Qwen4 exp Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/Qwen3.8-Flash-Next-4bit

Qwen3.8 Flash Next 4bit Parameters and Internals

LLM Name	Qwen3.8 Flash Next 4bit
Repository 🤗	https://huggingface.co/mlx-community/Qwen3.8-Flash-Next-4bit
Base Model(s)	Qwen/Qwen3.8-Flash-Next Qwen/Qwen3.8-Flash-Next
Model Size	177.4b
Required VRAM	111.2 GB
Updated	2026-09-03
Maintainer	mlx-community
Model Type	qwen4_exp
Model Files	5.3 GB: 1-of-22 5.2 GB: 2-of-22 5.2 GB: 3-of-22 5.2 GB: 4-of-22 5.2 GB: 5-of-22 5.2 GB: 6-of-22 5.1 GB: 7-of-22 5.3 GB: 8-of-22 5.3 GB: 9-of-22 5.0 GB: 10-of-22 5.3 GB: 11-of-22 5.0 GB: 12-of-22 5.3 GB: 13-of-22 5.3 GB: 14-of-22 5.0 GB: 15-of-22 5.3 GB: 16-of-22 5.0 GB: 17-of-22 5.3 GB: 18-of-22 5.3 GB: 19-of-22 5.0 GB: 20-of-22 5.3 GB: 21-of-22 2.1 GB: 22-of-22
Supported Languages	en
Quantization Type	4bit
Model Architecture	Qwen4ExpForConditionalGeneration
Model Max Length	262144
Transformers Version	5.8.0.dev0
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.8 Flash Next 4bit 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

Quantized Models of the Qwen3.8 Flash Next 4bit

Model	Likes	Downloads	VRAM
...8 Flash Next 141B A6B V4.0 Mlx	0	428	44 GB
... 119B A5B Niwaki V2.4 3bit Mlx	0	380	44 GB
...h Next 99B A5B Niwaki 3bit Mlx	2	267	0 GB
...lash Next Saikei V1.0 4bit Mlx	0	124	111 GB

Best Alternatives to Qwen3.8 Flash Next 4bit

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.8 Flash Next OptiQ 2bit	0K / 79.9 GB	671	1
...lash Next Saikei V1.0 4bit Mlx	0K / 111.8 GB	124	0
Qwen3.8 Flash Next JANG 1L	0K / 64.5 GB	637	2
Qwen3.8 Flash Next Heretic	0K / 355.1 GB	96	0
Qwen3.8 Flash Next Heretic 2	0K / 355.1 GB	64	3

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Qwen3.8-Flash-Next-4bit.