What are the hardware requirements for Mixtral Debug?

Mixtral Debug requires a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mixtral Debug and how large is it?

Mixtral Debug is developed by Phando, a model with 6.5m 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 Mixtral Debug?

Mixtral Debug is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mixtral Debug by Phando — 32K context

Name: Mixtral Debug
Author: Phando

Mixtral Debug is an open-source language model by Phando. Features: 6.5m LLM, Context: 32K, LLM Explorer Score: 0.13.

Arxiv:1910.09700 Autotrain compatible Endpoints compatible Mixtral Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Phando/mixtral-debug

Mixtral Debug Parameters and Internals

LLM Name	Mixtral Debug
Repository 🤗	https://huggingface.co/Phando/mixtral-debug
Model Size	6.5m
Required VRAM	0 GB
Updated	2025-04-25
Maintainer	Phando
Model Type	mixtral
Model Files	0.0 GB
Model Architecture	MixtralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float32

Rank the Mixtral Debug 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

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