What are the hardware requirements for Vicuna 33B Coder AWQ?

Vicuna 33B Coder AWQ requires approximately 17.6 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 Vicuna 33B Coder AWQ and how large is it?

Vicuna 33B Coder AWQ is developed by TheBloke, 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 Vicuna 33B Coder AWQ?

Vicuna 33B Coder AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Vicuna 33B Coder AWQ by TheBloke — VRAM 17.6GB, 2K context

Name: Vicuna 33B Coder AWQ
Author: TheBloke

Vicuna 33B Coder AWQ is an open-source language model by TheBloke. Features: 33b LLM, VRAM: 17.6GB, Context: 2K, License: other, Quantized, Code Generating, LLM Explorer Score: 0.09.

Arxiv:1910.09700 4-bit Awq Base model:felixchao/vicuna-33... Base model:quantized:felixchao... Code Codegen Llama Model-index Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/vicuna-33B-coder-AWQ

Vicuna 33B Coder AWQ Parameters and Internals

Model Type

text-generation

Additional Notes

AWQ is an efficient, accurate, and fast low-bit quantization method, supporting 4-bit quantization for this model.

LLM Name	Vicuna 33B Coder AWQ
Repository 🤗	https://huggingface.co/TheBloke/vicuna-33B-coder-AWQ
Model Name	Vicuna 33B Coder
Model Creator	Chao Chang-Yu
Base Model(s)	Vicuna 33B Coder FelixChao/vicuna-33b-coder
Model Size	33b
Required VRAM	17.6 GB
Updated	2026-07-24
Maintainer	TheBloke
Model Type	llama
Model Files	10.0 GB: 1-of-2 7.6 GB: 2-of-2
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	other
Context Length	2048
Model Max Length	2048
Transformers Version	4.34.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Vicuna 33B Coder AWQ 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 Vicuna 33B Coder AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Everyone Coder 33B Base AWQ	16K / 18.1 GB	8	2
...eepseek Coder 33B Instruct AWQ	16K / 18.1 GB	731	42
Deepseek Coder 33B Base AWQ	16K / 18.1 GB	22	4
...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 6.0bpw H6 EXL2	16K / 25.3 GB	8	0
...erpreter DS 33B 8.0bpw H8 EXL2	16K / 33.5 GB	5	1
...der 33B V2 Base 8.0bpw H8 EXL2	16K / 33.5 GB	1	1
... Coder 33B Base 6.0bpw H6 EXL2	16K / 25.3 GB	3	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/vicuna-33B-coder-AWQ.