What are the hardware requirements for Multimaster 7B V6?

Multimaster 7B V6 requires approximately 142.5 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Multimaster 7B V6 and how large is it?

Multimaster 7B V6 is developed by ibivibiv, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Multimaster 7B V6 perform on standard benchmarks?

Multimaster 7B V6 has the following published scores: MMLU 64.74. Compare against reference models on this page or on the LLM Explorer leaderboards.

Multimaster 7B V6 by ibivibiv — VRAM 142.5GB, 32K context

Name: Multimaster 7B V6
Author: ibivibiv

Multimaster 7B V6 is an open-source language model by ibivibiv. Features: 7b LLM, VRAM: 142.5GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.21, Arc: 72.8, HellaSwag: 88.8, MMLU: 64.7, GSM8K: 70.4.

Arxiv:1803.05457 Arxiv:1905.07830 Arxiv:1907.10641 Arxiv:2009.03300 Arxiv:2109.07958 Arxiv:2110.14168 En Endpoints compatible Mixtral Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ibivibiv/multimaster-7b-v6

Multimaster 7B V6 Parameters and Internals

Model Type

multimodal

Use Cases

Considerations:

This model is a focus on multi-disciplinary model tuning

Additional Notes

multimaster-7b is a lora tuned version with the adapter merged back into the main model

Supported Languages

English (Primary)

Input Output

Input Format:

alpaca style

Accepted Modalities:

text

LLM Name	Multimaster 7B V6
Repository 🤗	https://huggingface.co/ibivibiv/multimaster-7b-v6
Model Size	7b
Required VRAM	142.5 GB
Updated	2026-08-03
Maintainer	ibivibiv
Model Type	mixtral
Model Files	5.0 GB: 1-of-29 5.0 GB: 2-of-29 4.9 GB: 3-of-29 4.9 GB: 4-of-29 4.9 GB: 5-of-29 4.9 GB: 6-of-29 4.9 GB: 7-of-29 4.9 GB: 8-of-29 4.9 GB: 9-of-29 5.0 GB: 10-of-29 4.9 GB: 11-of-29 4.9 GB: 12-of-29 4.9 GB: 13-of-29 4.9 GB: 14-of-29 4.9 GB: 15-of-29 4.9 GB: 16-of-29 4.9 GB: 17-of-29 4.9 GB: 18-of-29 5.0 GB: 19-of-29 4.9 GB: 20-of-29 4.9 GB: 21-of-29 4.9 GB: 22-of-29 4.9 GB: 23-of-29 4.9 GB: 24-of-29 4.9 GB: 25-of-29 4.9 GB: 26-of-29 4.9 GB: 27-of-29 5.0 GB: 28-of-29 4.8 GB: 29-of-29
Supported Languages	en
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	float32

Rank the Multimaster 7B V6 capabilities

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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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