What are the hardware requirements for CodeLlama 7B Python 4bit MLX?

CodeLlama 7B Python 4bit MLX requires approximately 4 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 4bit MLX and how large is it?

CodeLlama 7B Python 4bit MLX is developed by mlx-community, 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 4bit MLX?

CodeLlama 7B Python 4bit MLX is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

CodeLlama 7B Python 4bit MLX by mlx-community — VRAM 4GB, 16K context

Name: CodeLlama 7B Python 4bit MLX
Author: mlx-community

CodeLlama 7B Python 4bit MLX is an open-source language model by mlx-community. Features: 7b LLM, VRAM: 4GB, Context: 16K, License: llama2, Quantized, Code Generating, LLM Explorer Score: 0.11.

4bit Code Codegen Llama Llama2 Mlx Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/mlx-community/CodeLlama-7b-Python-4bit-MLX

CodeLlama 7B Python 4bit MLX Parameters and Internals

Model Type

text generation

Additional Notes

This model was converted to MLX format

Supported Languages

Python (high proficiency)

Input Output

Input Format:

[INST] <> '<PROMPT_HERE>' <> [/INST]

Accepted Modalities:

text

Output Format:

text

Performance Tips:

For detailed verbosity, set `verbose=True` while generating text.

LLM Name	CodeLlama 7B Python 4bit MLX
Repository 🤗	https://huggingface.co/mlx-community/CodeLlama-7b-Python-4bit-MLX
Model Size	7b
Required VRAM	4 GB
Updated	2026-07-04
Maintainer	mlx-community
Model Type	llama
Model Files	4.0 GB
Supported Languages	code
Quantization Type	4bit
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.36.2
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the CodeLlama 7B Python 4bit MLX 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 CodeLlama 7B Python 4bit MLX

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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
...B Instruct Hf Bnb 4bit Smashed	16K / 4.2 GB	6	0
CodeLlama 7B Python Onnx Fp16	16K / GB	5	1
CodelLama7B Inst DPO 7K Mlx	16K / 4.2 GB	49	4
...eLlama 7B Instruct Hf 4bit MLX	16K / 4.2 GB	84	3
...pMagic Coder 7B 8.0bpw H8 EXL2	16K / 6.9 GB	3	1
CodeLlama 7B Fp16	16K / 13.5 GB	14	7

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/CodeLlama-7b-Python-4bit-MLX.