What are the hardware requirements for WizardCoder Python 34B V1.0 AWQ?

WizardCoder Python 34B V1.0 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 WizardCoder Python 34B V1.0 AWQ and how large is it?

WizardCoder Python 34B V1.0 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 WizardCoder Python 34B V1.0 AWQ?

WizardCoder Python 34B V1.0 AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

WizardCoder Python 34B V1.0 AWQ by TheBloke — VRAM 18.3GB, 16K context

Name: WizardCoder Python 34B V1.0 AWQ
Author: TheBloke

WizardCoder Python 34B V1.0 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:2303.08774 Arxiv:2304.12244 Arxiv:2306.08568 Arxiv:2308.09583 4-bit Awq Base model:quantized:wizardlmt... Base model:wizardlmteam/wizard... Code Codegen Llama Model-index Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/TheBloke/WizardCoder-Python-34B-V1.0-AWQ

WizardCoder Python 34B V1.0 AWQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

research, commercial applications

Applications:

code generation, text generation

Primary Use Cases:

enhanced code generation for Python

Additional Notes

The model utilizes advanced AWQ quantization for improved deployment efficiency.

Supported Languages

or_languages (Python)

Training Details

Data Sources:

Evol Instruct Code

Data Volume:

80k

Methodology:

Low-bit weight quantization (AWQ)

Context Length:

4096

Hardware Used:

1 x 48GB GPU, 2 x 80GB GPU

Model Architecture:

Transformer-based

Input Output

Input Format:

Instruction followed by a prompt and response format.

Accepted Modalities:

text

Output Format:

Textual code and task responses.

Performance Tips:

Use with proper quantization parameters for optimal performance.

Release Notes

Version:

1.0

Date:

2023/08/26

Notes:

Initial release of WizardCoder-Python-34B-V1.0 with AWQ quantization.

LLM Name	WizardCoder Python 34B V1.0 AWQ
Repository 🤗	https://huggingface.co/TheBloke/WizardCoder-Python-34B-V1.0-AWQ
Model Creator	WizardLM
Base Model(s)	WizardLM/WizardCoder-Python-34B-V1.0 WizardLM/WizardCoder-Python-34B-V1.0
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
AWQ Quantization	Yes
Quantization Type	awq
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32001
Torch Data Type	float16

Rank the WizardCoder Python 34B V1.0 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 WizardCoder Python 34B V1.0 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
CodeLlama 34B AWQ	16K / 18.3 GB	24	2
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/WizardCoder-Python-34B-V1.0-AWQ.