What are the hardware requirements for CodeLlama 7B Python AWQ?

CodeLlama 7B Python AWQ requires approximately 3.9 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed CodeLlama 7B Python AWQ and how large is it?

CodeLlama 7B Python AWQ is developed by TheBloke, a model with 7b 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 CodeLlama 7B Python AWQ?

CodeLlama 7B Python AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

CodeLlama 7B Python AWQ by TheBloke — VRAM 3.9GB, 16K context

Name: CodeLlama 7B Python AWQ
Author: TheBloke

CodeLlama 7B Python AWQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 3.9GB, Context: 16K, License: llama2, Quantized, Code Generating, LLM Explorer Score: 0.08.

Arxiv:2308.12950 4-bit Awq Code Codegen Llama Llama2 Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/CodeLlama-7B-Python-AWQ

CodeLlama 7B Python AWQ Parameters and Internals

Model Type

llama

Training Details

Hardware Used:

A100-80GB GPUs

Model Architecture:

Optimized transformer architecture

Input Output

Input Format:

Models input text only.

Output Format:

Models generate text only.

LLM Name	CodeLlama 7B Python AWQ
Repository 🤗	https://huggingface.co/TheBloke/CodeLlama-7B-Python-AWQ
Model Name	CodeLlama 7B Python
Model Creator	Meta
Base Model(s)	codellama/CodeLlama-7b-python-hf codellama/CodeLlama-7b-python-hf
Model Size	7b
Required VRAM	3.9 GB
Updated	2026-07-26
Maintainer	TheBloke
Model Type	llama
Model Files	3.9 GB
Supported Languages	code
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.33.0.dev0
Tokenizer Class	CodeLlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the CodeLlama 7B Python 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

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Best Alternatives	Context / RAM	Downloads	Likes
CodeLlama 7B Instruct AWQ	16K / 3.9 GB	278	4
CodeLlama 7B AWQ	16K / 3.9 GB	75	6
...Llama 7B Python Hf W4 G128 AWQ	16K / 3.9 GB	8	0
...ama 7B Instruct Hf W4 G128 AWQ	16K / 3.9 GB	6	0
Llama 2 Coder 7B AWQ	4K / 3.9 GB	8	3
...eepseek Coder 7B Base V1.5 AWQ	4K / 4.8 GB	0	0
CodeLlama 7B Java 16bit	16K / 13.5 GB	10	0
Codellama 7B Bnb 4bit	16K / 3.9 GB	3695	9
...ruct Solidity Bnb 4bit Smashed	16K / 4.2 GB	6	0
...lama 7B Tofuagent Contpretrain	16K / 13.5 GB	6	0

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/CodeLlama-7B-Python-AWQ.