What are the hardware requirements for Nanbeige 16B Base 32K GGUF?

Nanbeige 16B Base 32K GGUF requires approximately 6.6 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nanbeige 16B Base 32K GGUF and how large is it?

Nanbeige 16B Base 32K GGUF is developed by TheBloke, a model with 16b 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 Nanbeige 16B Base 32K GGUF?

Nanbeige 16B Base 32K GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nanbeige 16B Base 32K GGUF by TheBloke — VRAM 6.6GB

Name: Nanbeige 16B Base 32K GGUF
Author: TheBloke

Nanbeige 16B Base 32K GGUF is an open-source language model by TheBloke. Features: 16b LLM, VRAM: 6.6GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

Custom code En Gguf Nanbeige Quantized Region:us Zh

Model Card on HF 🤗: https://huggingface.co/TheBloke/Nanbeige-16B-Base-32K-GGUF

Nanbeige 16B Base 32K GGUF Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

Research, Commercial applications

Applications:

Text generation

Primary Use Cases:

Handling longer text contexts up to 32k tokens

Limitations:

Includes potential biases and unexpected outputs, Exemplifies harmful content, Model size and probabilistic generation can limit output expectations

Considerations:

Avoid propagation of harmful output content.

Additional Notes

Base-32k version is recommended for handling long context tasks.

Supported Languages

en (proficient), zh (proficient)

Training Details

Data Sources:

High-quality internet corpus, Various books, Code

Data Volume:

2.5T Tokens

Methodology:

YaRN interpolation method for position encoding

Context Length:

32000

Model Architecture:

Nanbeige-16B with YaRN encoding

Input Output

Accepted Modalities:

text

Release Notes

Version:

Base-32k

Notes:

Full parameter incremental pre-training with 20B tokens of Chinese, English, and code corpora, under 32k max length.

LLM Name	Nanbeige 16B Base 32K GGUF
Repository 🤗	https://huggingface.co/TheBloke/Nanbeige-16B-Base-32K-GGUF
Model Name	Nanbeige 16B Base 32K
Model Creator	Nanbeige LLM Lab
Base Model(s)	Nanbeige/Nanbeige-16B-Base-32K Nanbeige/Nanbeige-16B-Base-32K
Model Size	16b
Required VRAM	6.6 GB
Updated	2026-08-03
Maintainer	TheBloke
Model Type	nanbeige
Model Files	6.6 GB 8.4 GB 7.7 GB 6.9 GB 9.0 GB 9.6 GB 9.0 GB 10.9 GB 11.2 GB 10.9 GB 13.0 GB 16.8 GB
Supported Languages	en zh
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	apache-2.0

Rank the Nanbeige 16B Base 32K GGUF 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 Nanbeige 16B Base 32K GGUF

Best Alternatives	Context / RAM	Downloads	Likes
Tinyllama Gguf 16B	0K / 2.2 GB	17	0
Llama 3 16B Instruct V0.1 GGUF	0K / 6.4 GB	502	9
Nanbeige 16B Chat 32K GGUF	0K / 6.6 GB	566	6
Nanbeige 16B Base GGUF	0K / 6.6 GB	200	1
Nanbeige 16B Chat GGUF	0K / 6.6 GB	159	1
Ct2fast Codegen2 16B	0K / 32.1 GB	0	1
Ct2fast Codegen 16B Mono	0K / 32.1 GB	1	2

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Nanbeige-16B-Base-32K-GGUF.