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

CodeLlama 70B Instruct 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 Instruct AWQ and how large is it?

CodeLlama 70B Instruct 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 Instruct AWQ?

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

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

Name: CodeLlama 70B Instruct AWQ
Author: TheBloke

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

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

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

CodeLlama 70B Instruct AWQ Parameters and Internals

Model Type

Instruct, text generation

Use Cases

Areas:

commercial, research

Applications:

code synthesis, code understanding, code assistant, generation applications

Limitations:

use in languages other than English, use that violates laws or regulations

Additional Notes

Note: Use of this model is governed by the Meta license. Future versions will be improved based on community feedback.

Training Details

Context Length:

16000

Hardware Used:

A100-80GB GPUs

Model Architecture:

auto-regressive language model utilizing an optimized transformer architecture.

Input Output

Output Format:

text

LLM Name	CodeLlama 70B Instruct AWQ
Repository 🤗	https://huggingface.co/TheBloke/CodeLlama-70B-Instruct-AWQ
Model Name	Codellama 70B Instruct
Model Creator	Code Llama
Base Model(s)	CodeLlama 70B Instruct Hf codellama/CodeLlama-70b-Instruct-hf
Model Size	70b
Required VRAM	36.6 GB
Updated	2026-08-05
Maintainer	TheBloke
Model Type	llama
Instruction-Based	Yes
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 Instruct 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 Instruct AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...Llama 70B Instruct Hf 4bit MLX	4K / 39.1 GB	417	25
...70B Instruct Nf4 Fp16 Upscaled	4K / 138.7 GB	10	1
...70B Instruct Hf 5.0bpw H6 EXL2	2K / 43.6 GB	5	6
...70B Instruct Hf 2.4bpw H6 EXL2	2K / 21.3 GB	6	1
...0B Instruct Hf 2.65bpw H6 EXL2	2K / 23.4 GB	5	3
...70B Instruct Hf 4.0bpw H6 EXL2	2K / 35.1 GB	6	1
CodeLlama 70B Instruct Hf	4K / 72.3 GB	729	24
Code Llama 70B Python Instruct	4K / 138.1 GB	5	1
CodeLlama 70B Instruct Hf	4K / 72.3 GB	463	210
CodeLlama 70B Instruct Hf GGUF	4K / 25.5 GB	487	2

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