What are the hardware requirements for Qwen3.8 Flash Next MLX Q6s?

Qwen3.8 Flash Next MLX Q6s requires approximately 103.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 Flash Next MLX Q6s and how large is it?

Qwen3.8 Flash Next MLX Q6s is developed by inferencerlabs. 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 MLX Q6s?

Qwen3.8 Flash Next MLX Q6s 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 MLX Q6s by inferencerlabs — VRAM 103.6GB

Name: Qwen3.8 Flash Next MLX Q6s
Author: inferencerlabs

Qwen3.8 Flash Next MLX Q6s is an open-source language model by inferencerlabs. Features: LLM, VRAM: 103.6GB, LLM Explorer Score: 0.32.

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

Model Card on HF 🤗: https://huggingface.co/inferencerlabs/Qwen3.8-Flash-Next-MLX-Q6s

Qwen3.8 Flash Next MLX Q6s Parameters and Internals

LLM Name	Qwen3.8 Flash Next MLX Q6s
Repository 🤗	https://huggingface.co/inferencerlabs/Qwen3.8-Flash-Next-MLX-Q6s
Base Model(s)	Qwen/Qwen3.8-Flash-Next Qwen/Qwen3.8-Flash-Next
Required VRAM	103.6 GB
Updated	2026-10-27
Maintainer	inferencerlabs
Model Type	qwen4_exp
Model Files	5.0 GB: 1-of-33 0.7 GB: 2-of-33 3.6 GB: 13-of-33 5.0 GB: 14-of-33 4.9 GB: 15-of-33 4.9 GB: 16-of-33 5.0 GB: 17-of-33 4.9 GB: 18-of-33 4.9 GB: 19-of-33 5.0 GB: 20-of-33 4.9 GB: 21-of-33 4.9 GB: 22-of-33 5.0 GB: 23-of-33 4.9 GB: 24-of-33 4.9 GB: 25-of-33 5.0 GB: 26-of-33 4.9 GB: 27-of-33 4.9 GB: 28-of-33 5.0 GB: 29-of-33 4.9 GB: 30-of-33 4.9 GB: 31-of-33 5.0 GB: 32-of-33 0.5 GB: 33-of-33
Supported Languages	en
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 MLX Q6s 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

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Best Alternatives	Context / RAM	Downloads	Likes
....8 Flash Next Orinfer E8P Q2A8	0K / GB	29	1
CYBER FROST 3.8 HGN	0K / GB	40	4
Tinfield 1 Exl3	0K / GB	52	2
...A16 AutoRound MTP INT4 Experts	0K / 1.5 GB	54	1
Qwen3.8 Flash Next MLX Q9	0K / 200.6 GB	3888	1
Qwen3.8 Flash Next MLX Q4	0K / 104.3 GB	3382	1
...wen3.8 Flash Next Coder Cut240	0K / 4.5 GB	4622	2
Qwen3.8 Flash Next APEX GGUF	0K / 0.5 GB	2691	7
....8 Flash Next Mixed Quant GGUF	0K / GB	2325	3

Note: green Score (e.g. "73.2") means that the model is better than inferencerlabs/Qwen3.8-Flash-Next-MLX-Q6s.