What are the hardware requirements for Qwen3.8 Flash Next REAP 288 MLX 4bit?

Qwen3.8 Flash Next REAP 288 MLX 4bit requires approximately 36.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.8 Flash Next REAP 288 MLX 4bit and how large is it?

Qwen3.8 Flash Next REAP 288 MLX 4bit is developed by sh0wie, a model with 21.2b 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 REAP 288 MLX 4bit?

Qwen3.8 Flash Next REAP 288 MLX 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 REAP 288 MLX 4bit by sh0wie — VRAM 36.2GB

Name: Qwen3.8 Flash Next REAP 288 MLX 4bit
Author: sh0wie

Qwen3.8 Flash Next REAP 288 MLX 4bit is an open-source language model by sh0wie. Features: 21.2b LLM, VRAM: 36.2GB, License: other, Quantized, LLM Explorer Score: 0.38.

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

Model Card on HF 🤗: https://huggingface.co/sh0wie/Qwen3.8-Flash-Next-REAP-288-MLX-4bit

Qwen3.8 Flash Next REAP 288 MLX 4bit Parameters and Internals

LLM Name	Qwen3.8 Flash Next REAP 288 MLX 4bit
Repository 🤗	https://huggingface.co/sh0wie/Qwen3.8-Flash-Next-REAP-288-MLX-4bit
Base Model(s)	Qwen/Qwen3.8-Flash-Next Qwen/Qwen3.8-Flash-Next
Model Size	21.2b
Required VRAM	36.2 GB
Updated	2026-08-30
Maintainer	sh0wie
Model Type	qwen4_exp
Model Files	0.5 GB: 1-of-131 0.5 GB: 2-of-131 0.3 GB: 3-of-131 0.5 GB: 4-of-131 0.8 GB: 5-of-131 1.0 GB: 6-of-131 1.0 GB: 7-of-131 1.0 GB: 8-of-131 1.0 GB: 9-of-131 1.0 GB: 10-of-131 1.0 GB: 11-of-131 1.0 GB: 12-of-131 1.0 GB: 13-of-131 1.0 GB: 14-of-131 1.0 GB: 15-of-131 1.0 GB: 16-of-131 1.0 GB: 17-of-131 1.0 GB: 18-of-131 1.0 GB: 19-of-131 1.0 GB: 20-of-131 1.0 GB: 21-of-131 1.0 GB: 22-of-131 1.0 GB: 23-of-131 1.0 GB: 24-of-131 1.0 GB: 25-of-131 1.0 GB: 26-of-131 1.0 GB: 27-of-131 1.0 GB: 28-of-131 1.0 GB: 29-of-131 1.0 GB: 30-of-131 1.0 GB: 31-of-131 1.0 GB: 32-of-131 1.0 GB: 33-of-131 1.0 GB: 34-of-131 1.0 GB: 35-of-131 1.0 GB: 36-of-131 0.5 GB: 37-of-131 0.5 GB: 38-of-131 0.3 GB: 39-of-131 0.5 GB: 40-of-131 0.3 GB: 41-of-131 0.5 GB: 42-of-131
Quantization Type	4bit
Model Architecture	Qwen4ExpForConditionalGeneration
License	other
Transformers Version	5.8.0.dev0

Rank the Qwen3.8 Flash Next REAP 288 MLX 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

Best Alternatives to Qwen3.8 Flash Next REAP 288 MLX 4bit

Best Alternatives	Context / RAM	Downloads	Likes
...8 Flash Next REAM 288 MLX 4bit	0K / 35.7 GB	586	1