What are the hardware requirements for Sbzhanzhang?

Sbzhanzhang requires approximately 2.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Sbzhanzhang and how large is it?

Sbzhanzhang is developed by AIXF, a model with 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 Sbzhanzhang?

Sbzhanzhang is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Sbzhanzhang by AIXF — VRAM 2.4GB

Name: Sbzhanzhang
Author: AIXF

Sbzhanzhang is an open-source language model by AIXF. Features: 4b LLM, VRAM: 2.4GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.3.

4-bit 4bit Base model:adapter:qwen/qwen3.... Base model:qwen/qwen3.5-4b Chinese Conversational Lora Mlx Quantized Qwen3.5 Qwen3 5 Region:us Role-play Safetensors Zh

Model Card on HF 🤗: https://huggingface.co/AIXF/sbzhanzhang

Sbzhanzhang Parameters and Internals

LLM Name	Sbzhanzhang
Repository 🤗	https://huggingface.co/AIXF/sbzhanzhang
Model Name	sb痛失姓名的站长
Base Model(s)	Qwen/Qwen3.5-4B Qwen/Qwen3.5-4B
Model Size	4b
Required VRAM	2.4 GB
Updated	2026-10-09
Maintainer	AIXF
Model Type	qwen3_5
Model Files	2.4 GB
Supported Languages	zh
Quantization Type	4bit
Model Architecture	Qwen3_5ForConditionalGeneration
License	apache-2.0
Model Max Length	262144
Transformers Version	4.57.0.dev0
Tokenizer Class	Qwen3_5Tokenizer
Padding Token	<\|endoftext\|>
Errors	replace

Rank the Sbzhanzhang 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 Sbzhanzhang

Best Alternatives	Context / RAM	Downloads	Likes
Underdog Woof 4B 1.1	0K / 2.4 GB	1607	22
Qwen3.5 4B MLX 4bit	0K / 3 GB	28023	32
Qwen3.5 4B OptiQ 4bit	0K / 0.1 GB	7823	23
Qwen3.5 4B 4bit Abliterated	0K / 3 GB	85	1
Fara1.5 4B OptiQ 4bit	0K / 3.5 GB	215	2
Qwen3.5 4B OQ4e FP16 MTP MLX	0K / 3.3 GB	42	1
...aude 4.6 Opus Abliterated 4bit	0K / 3 GB	516	5
...aude 4.6 Opus Abliterated 6bit	0K / 4.1 GB	188	3
Qwen3.5 4B Mlx 4bit	0K / 2.4 GB	16	3
Qwopus3.5 4B V3 4bit	0K / 3 GB	35	1

Note: green Score (e.g. "73.2") means that the model is better than AIXF/sbzhanzhang.