What are the hardware requirements for Chinese Alpaca Plus 33B Merged?

Chinese Alpaca Plus 33B Merged requires approximately 65.7 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Chinese Alpaca Plus 33B Merged and how large is it?

Chinese Alpaca Plus 33B Merged is developed by minlik, 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 Chinese Alpaca Plus 33B Merged?

Chinese Alpaca Plus 33B Merged is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Chinese Alpaca Plus 33B Merged by minlik — VRAM 65.7GB, 2K context

Name: Chinese Alpaca Plus 33B Merged
Author: minlik

Chinese Alpaca Plus 33B Merged is an open-source language model by minlik. Features: 33b LLM, VRAM: 65.7GB, Context: 2K, LLM Explorer Score: 0.08.

Endpoints compatible Llama Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/minlik/chinese-alpaca-plus-33b-merged

Chinese Alpaca Plus 33B Merged Parameters and Internals

Model Type

Language Generation

Supported Languages

Chinese (Advanced)

Training Details

Methodology:

加入中文词表，继续预训练中文Embedding并使用指令数据集进行finetuning。

Input Output

Input Format:

Prompt containing instructions and questions.

Accepted Modalities:

text

Output Format:

Generated text response.

Performance Tips:

Ensure you are using a CUDA-enabled GPU for optimal performance.

LLM Name	Chinese Alpaca Plus 33B Merged
Repository 🤗	https://huggingface.co/minlik/chinese-alpaca-plus-33b-merged
Model Size	33b
Required VRAM	65.7 GB
Updated	2026-08-08
Maintainer	minlik
Model Type	llama
Model Files	10.1 GB: 1-of-7 10.0 GB: 2-of-7 9.9 GB: 3-of-7 9.9 GB: 4-of-7 9.9 GB: 5-of-7 10.0 GB: 6-of-7 5.9 GB: 7-of-7 10.1 GB: 1-of-7 10.0 GB: 2-of-7 9.9 GB: 3-of-7 9.9 GB: 4-of-7 9.9 GB: 5-of-7 10.0 GB: 6-of-7 6.1 GB: 7-of-7
Model Architecture	LlamaForCausalLM
Context Length	2048
Model Max Length	2048
Transformers Version	4.29.0.dev0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	49954
Torch Data Type	float16

Rank the Chinese Alpaca Plus 33B Merged 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 Chinese Alpaca Plus 33B Merged

Best Alternatives	Context / RAM	Downloads	Likes
Llm Jp 4 33B Thinking	64K / 66.8 GB	192	24
Llm Jp 4 33B Base	64K / 66.8 GB	89	8
Llm Jp 4 33B Thinking NVFP4	64K / 21.6 GB	79	1
Llm Jp 4 33B Thinking Nvfp4	64K / 21.5 GB	38	2
...angled Llama 33M 32K Base V0.1	32K / 0.1 GB	22	1
ReflectionCoder DS 33B	16K / 67 GB	8293	4
Deepseek Wizard 33B Slerp	16K / 35.3 GB	7	0
ValidateAI 33B Slerp	16K / 35.4 GB	7	0
ValidateAI 3 33B Ties	16K / 66.5 GB	7	0
ValidateAI 2 33B AT	16K / 66.5 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than minlik/chinese-alpaca-plus-33b-merged.