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

CodeLlama 7B Python GGUF requires approximately 2.8 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

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

CodeLlama 7B Python GGUF 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 GGUF?

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

CodeLlama 7B Python GGUF by TheBloke — VRAM 2.8GB

Name: CodeLlama 7B Python GGUF
Author: TheBloke

CodeLlama 7B Python GGUF is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 2.8GB, License: llama2, Quantized, Code Generating, LLM Explorer Score: 0.1.

Arxiv:2308.12950 Code Codegen Gguf Llama Llama2 Quantized Region:us

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

CodeLlama 7B Python GGUF Parameters and Internals

Model Type

llama

Additional Notes

This model is designed for general code synthesis and understanding, specifically for Python.

LLM Name	CodeLlama 7B Python GGUF
Repository 🤗	https://huggingface.co/TheBloke/CodeLlama-7B-Python-GGUF
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	2.8 GB
Updated	2026-07-28
Maintainer	TheBloke
Model Type	llama
Model Files	2.8 GB 3.6 GB 3.3 GB 3.0 GB 3.8 GB 4.1 GB 3.9 GB 4.7 GB 4.8 GB 4.7 GB 5.5 GB 7.2 GB
Supported Languages	code
GGUF Quantization	Yes
Quantization Type	gguf
Generates Code	Yes
Model Architecture	AutoModel
License	llama2

Rank the CodeLlama 7B Python 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

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