What are the hardware requirements for CodeLlama 70B Python AWQ?

CodeLlama 70B Python AWQ requires approximately 36.6 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed CodeLlama 70B Python AWQ and how large is it?

CodeLlama 70B Python AWQ is developed by TheBloke, a model with 70b 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 70B Python AWQ?

CodeLlama 70B Python AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

CodeLlama 70B Python AWQ by TheBloke — VRAM 36.6GB, 4K context

Name: CodeLlama 70B Python AWQ
Author: TheBloke

CodeLlama 70B Python AWQ is an open-source language model by TheBloke. Features: 70b LLM, VRAM: 36.6GB, Context: 4K, License: llama2, Quantized, Code Generating, LLM Explorer Score: 0.11.

Arxiv:2308.12950 4-bit Awq Base model:codellama/codellama... Base model:quantized:codellama... Code Codegen Llama Llama2 Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/CodeLlama-70B-Python-AWQ

CodeLlama 70B Python AWQ Parameters and Internals

Model Type

llama

Use Cases

Primary Use Cases:

Code synthesis, Python programming

Limitations:

Use in languages other than English is out-of-scope

Training Details

Methodology:

AWQ - 4-bit low-bit weight quantization

Context Length:

16000

Hardware Used:

A100-80GB GPUs

Model Architecture:

Optimized transformer architecture

Input Output

Input Format:

Text input

Accepted Modalities:

text

Output Format:

Text output

LLM Name	CodeLlama 70B Python AWQ
Repository 🤗	https://huggingface.co/TheBloke/CodeLlama-70B-Python-AWQ
Model Name	CodeLlama 70B Python
Model Creator	Code Llama
Base Model(s)	CodeLlama 70B Python Hf codellama/CodeLlama-70b-Python-hf
Model Size	70b
Required VRAM	36.6 GB
Updated	2026-07-23
Maintainer	TheBloke
Model Type	llama
Model Files	9.9 GB: 1-of-4 9.9 GB: 2-of-4 9.9 GB: 3-of-4 6.9 GB: 4-of-4
Supported Languages	code
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	4096
Model Max Length	4096
Transformers Version	4.37.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32016
Torch Data Type	float16

Rank the CodeLlama 70B 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

Best Alternatives to CodeLlama 70B Python AWQ

Best Alternatives	Context / RAM	Downloads	Likes
CodeLlama 70B Hf AWQ	16K / 36.6 GB	13	4
CodeLlama 70B Instruct AWQ	4K / 36.6 GB	297	13
...rpreter CL 70B 4.65bpw H6 EXL2	16K / 40.6 GB	5	0
CodeLlama 70B Hf 4bit MLX	16K / 39.1 GB	112	12
...odeLlama 70B Hf 4.0bpw H6 EXL2	16K / 35 GB	4	1
...odeLlama 70B Hf 2.4bpw H6 EXL2	16K / 21.3 GB	3	1
CodeLLaMA 70B Hf Fp16	16K / 138.7 GB	8	2
...Llama 70B Instruct Hf 4bit MLX	4K / 39.1 GB	417	25
...deLlama 70B Python Hf 4bit MLX	4K / 39.1 GB	108	11
...70B Instruct Nf4 Fp16 Upscaled	4K / 138.7 GB	10	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/CodeLlama-70B-Python-AWQ.