What are the hardware requirements for Qwen3.5 2B 4bit Slim?

Qwen3.5 2B 4bit Slim requires approximately 1.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Qwen3.5 2B 4bit Slim and how large is it?

Qwen3.5 2B 4bit Slim is developed by nikimori, a model with 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 Qwen3.5 2B 4bit Slim?

Qwen3.5 2B 4bit Slim is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Qwen3.5 2B 4bit Slim by nikimori — VRAM 1.1GB

Name: Qwen3.5 2B 4bit Slim
Author: nikimori

Qwen3.5 2B 4bit Slim is an open-source language model by nikimori. Features: 2b LLM, VRAM: 1.1GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.31.

4-bit 4bit Base model:mlx-community/qwen3... Base model:quantized:mlx-commu... Conversational Mlx Quantized Qwen3 5 Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/nikimori/Qwen3.5-2B-4bit-slim

Qwen3.5 2B 4bit Slim Parameters and Internals

LLM Name	Qwen3.5 2B 4bit Slim
Repository 🤗	https://huggingface.co/nikimori/Qwen3.5-2B-4bit-slim
Base Model(s)	mlx-community/Qwen3.5-2B-4bit mlx-community/Qwen3.5-2B-4bit
Model Size	2b
Required VRAM	1.1 GB
Updated	2026-10-21
Maintainer	nikimori
Model Type	qwen3_5
Model Files	1.1 GB
Quantization Type	4bit
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	4.57.0.dev0
Tokenizer Class	TokenizersBackend
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Qwen3.5 2B 4bit Slim 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 Qwen3.5 2B 4bit Slim

Best Alternatives	Context / RAM	Downloads	Likes
Qwen3.5 2B M40 6bit	0K / 1.5 GB	463	1
Qwen3.5 2B Base 6bit	0K / 1.5 GB	417	1
Loopl 2B 4bit	0K / 1.7 GB	137	1
Qwen3.5 2B MLX 4bit	0K / 1.7 GB	12310	2
Qwen3.8 2B Distill Mlx 5Bit	0K / 1.3 GB	387	1
Qwen3.5 2B 6bit	0K / 2.2 GB	8680	7
Mavery Geselle 2B MLX 4bit	0K / 1.7 GB	77	2
Qwen3.5 2B 4bit	0K / 1.7 GB	5374	5
Qwen3.5 2B OptiQ 4bit	0K / 0.7 GB	1296	12
Spartan 1.2 2B MLX 8bit	0K / 1.1 GB	27	0

Note: green Score (e.g. "73.2") means that the model is better than nikimori/Qwen3.5-2B-4bit-slim.