What are the hardware requirements for Nanbeige4.3 33B MLX 4bit?

Nanbeige4.3 33B MLX 4bit requires approximately 18.7 GB of VRAM and supports a context window of 512K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nanbeige4.3 33B MLX 4bit and how large is it?

Nanbeige4.3 33B MLX 4bit is developed by Nurymanau, a model with 33b 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 Nanbeige4.3 33B MLX 4bit?

Nanbeige4.3 33B MLX 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nanbeige4.3 33B MLX 4bit by Nurymanau — VRAM 18.7GB, 512K context

Name: Nanbeige4.3 33B MLX 4bit
Author: Nurymanau

Nanbeige4.3 33B MLX 4bit is an open-source language model by Nurymanau. Features: 33b LLM, VRAM: 18.7GB, Context: 512K, License: apache-2.0, Quantized, LLM Explorer Score: 0.32.

4-bit 4bit Base model:nanbeige/nanbeige4.... Base model:quantized:nanbeige/... Conversational En Llama Mlx Nanbeige Quantized Region:us Safetensors Sharded Tensorflow Zh

Model Card on HF 🤗: https://huggingface.co/Nurymanau/Nanbeige4.3-33B-MLX-4bit

Nanbeige4.3 33B MLX 4bit Parameters and Internals

LLM Name	Nanbeige4.3 33B MLX 4bit
Repository 🤗	https://huggingface.co/Nurymanau/Nanbeige4.3-33B-MLX-4bit
Base Model(s)	Nanbeige/Nanbeige4.3-33B Nanbeige/Nanbeige4.3-33B
Model Size	33b
Required VRAM	18.7 GB
Updated	2026-10-28
Maintainer	Nurymanau
Model Type	llama
Model Files	1.1 GB: 1-of-14 1.4 GB: 2-of-14 1.4 GB: 3-of-14 1.4 GB: 4-of-14 1.3 GB: 5-of-14 1.4 GB: 6-of-14 1.3 GB: 7-of-14 1.4 GB: 8-of-14 1.4 GB: 9-of-14 1.4 GB: 10-of-14 1.4 GB: 11-of-14 1.3 GB: 12-of-14 1.4 GB: 13-of-14 1.1 GB: 14-of-14
Supported Languages	en zh
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	524288
Model Max Length	524288
Transformers Version	4.51.1
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	166912
Torch Data Type	bfloat16

Rank the Nanbeige4.3 33B 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 Nanbeige4.3 33B MLX 4bit

Best Alternatives	Context / RAM	Downloads	Likes
Nanbeige4.3 33B MLX 4bit	512K / 18.6 GB	628	8
...Interpreter DS 33B Hf 4bit Mlx	16K / 19.1 GB	270	7
...erpreter DS 33B 4.0bpw H6 EXL2	16K / 17.1 GB	8	4
...rpreter DS 33B 4.65bpw H6 EXL2	16K / 19.8 GB	5	3
...erpreter DS 33B 5.0bpw H6 EXL2	16K / 21.2 GB	6	1
...erpreter DS 33B 8.0bpw H8 EXL2	16K / 33.5 GB	5	1
...erpreter DS 33B 6.0bpw H6 EXL2	16K / 25.3 GB	8	0
...e DeepSeek 33B 4.65bpw H6 EXL2	16K / 19.8 GB	7	2
...se DeepSeek 33B 4.0bpw H6 EXL2	16K / 17.1 GB	5	2
...se DeepSeek 33B 8.0bpw H8 EXL2	16K / 33.5 GB	3	2

Note: green Score (e.g. "73.2") means that the model is better than Nurymanau/Nanbeige4.3-33B-MLX-4bit.