What are the hardware requirements for CodeLlama 34B AWQ?

CodeLlama 34B AWQ requires approximately 18.3 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 34B AWQ and how large is it?

CodeLlama 34B AWQ is developed by TheBloke, a model with 34b 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 34B AWQ?

CodeLlama 34B AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

CodeLlama 34B AWQ by TheBloke — VRAM 18.3GB, 16K context

Name: CodeLlama 34B AWQ
Author: TheBloke

CodeLlama 34B AWQ is an open-source language model by TheBloke. Features: 34b LLM, VRAM: 18.3GB, Context: 16K, License: llama2, Quantized, Code Generating, LLM Explorer Score: 0.09.

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-34B-AWQ

CodeLlama 34B AWQ Parameters and Internals

Model Type

llama

Use Cases

Areas:

commercial, research

Primary Use Cases:

code synthesis, code understanding

Limitations:

Use in any manner that violates applicable laws., Use in languages other than English.

Considerations:

Developers should perform safety testing and tuning tailored to their specific applications of the model.

Additional Notes

This model is designed for general code synthesis and understanding.

Training Details

Model Architecture:

Code Llama is an auto-regressive language model that uses an optimized transformer architecture.

Responsible Ai Considerations

Fairness:

Testing conducted to date has been in English and may not cover all scenarios.

Transparency:

Potential outputs cannot be predicted in advance.

Mitigation Strategies:

Safety testing and tuning are recommended before deployment.

LLM Name	CodeLlama 34B AWQ
Repository 🤗	https://huggingface.co/TheBloke/CodeLlama-34B-AWQ
Model Name	CodeLlama 34B
Model Creator	Meta
Base Model(s)	CodeLlama 34B Hf codellama/CodeLlama-34b-hf
Model Size	34b
Required VRAM	18.3 GB
Updated	2026-08-08
Maintainer	TheBloke
Model Type	llama
Model Files	9.9 GB: 1-of-2 8.4 GB: 2-of-2
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	4.32.0.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 34B 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 34B AWQ

Best Alternatives	Context / RAM	Downloads	Likes
...echless Codellama 34B V2.0 AWQ	16K / 18.3 GB	6	6
Phind CodeLlama 34B V2 AWQ	16K / 18.3 GB	42	35
...enbuddy Coder 34B V11 Bf16 AWQ	16K / 18.5 GB	4	1
CodeLlama 34B Instruct AWQ	16K / 18.3 GB	57	1
...izardCoder Python 34B V1.0 AWQ	16K / 18.3 GB	11	6
MAmmoTH Coder 34B AWQ	16K / 18.3 GB	4	1
CodeFuse CodeLlama 34B AWQ	16K / 18.3 GB	11	2
CodeLlama 34B Python AWQ	16K / 18.3 GB	8	2
...nd CodeLlama 34B Python V1 AWQ	16K / 18.3 GB	7	2
Phind CodeLlama 34B V1 AWQ	16K / 18.3 GB	6	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/CodeLlama-34B-AWQ.