What are the hardware requirements for CodeLlama 34B Guanaco?

CodeLlama 34B Guanaco requires approximately 67.5 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 Guanaco and how large is it?

CodeLlama 34B Guanaco is developed by mzbac, 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 Guanaco?

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

CodeLlama 34B Guanaco by mzbac — VRAM 67.5GB, 16K context

Name: CodeLlama 34B Guanaco
Author: mzbac

CodeLlama 34B Guanaco is an open-source language model by mzbac. Features: 34b LLM, VRAM: 67.5GB, Context: 16K, License: mit, Code Generating, LLM Explorer Score: 0.1.

Codegen Endpoints compatible Llama Pytorch Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/mzbac/CodeLlama-34b-guanaco

CodeLlama 34B Guanaco Parameters and Internals

Model Type

fine-tuned, text generation

Use Cases

Limitations:

struggles to determine the end of the answer

Training Details

Data Sources:

OpenAssistant-Guanaco dataset

Methodology:

fine-tuned on text chunks instead of Q&A pairs

Input Output

Input Format:

### Human: {prompt} ### Assistant:

Accepted Modalities:

text

Performance Tips:

Recommend using a stop string like "### Human:" to prevent the model from talking to itself.

LLM Name	CodeLlama 34B Guanaco
Repository 🤗	https://huggingface.co/mzbac/CodeLlama-34b-guanaco
Model Size	34b
Required VRAM	67.5 GB
Updated	2026-07-04
Maintainer	mzbac
Model Type	llama
Model Files	9.8 GB: 1-of-7 9.7 GB: 2-of-7 9.7 GB: 3-of-7 9.7 GB: 4-of-7 9.7 GB: 5-of-7 9.7 GB: 6-of-7 9.2 GB: 7-of-7
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	mit
Context Length	16384
Model Max Length	16384
Transformers Version	4.34.0
Tokenizer Class	CodeLlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the CodeLlama 34B Guanaco 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

Quantized Models of the CodeLlama 34B Guanaco

Model	Likes	Downloads	VRAM
CodeLlama 34B Guanaco Gptq	5	65	18 GB

Best Alternatives to CodeLlama 34B Guanaco

Best Alternatives	Context / RAM	Downloads	Likes
...gpt 32K Codellama 34B Instruct	32K / 67.5 GB	56	2
CodeLlama 34B Instruct Hf	16K / 67.5 GB	22872	304
CodeLlama 34B Instruct Hf	16K / 1.4 GB	7	3
CodeLlama 34B Instruct Hf	16K / 1.4 GB	5	3
ReflectionCoder CL 34B	16K / 67.6 GB	7735	0
Speechless Codellama 34B V2.0	16K / 67.5 GB	96	17
CodeLlama 34B Hf	16K / 67.5 GB	27673	178
Phind CodeLlama 34B V2	16K / 67.5 GB	618	834
Phind CodeLlama 34B V1	16K / 67.5 GB	165	320
Phind CodeLlama 34B Python V1	16K / 67.5 GB	180	252

Note: green Score (e.g. "73.2") means that the model is better than mzbac/CodeLlama-34b-guanaco.