What are the hardware requirements for Supermario V4?

Supermario V4 requires approximately 14.4 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 Supermario V4 and how large is it?

Supermario V4 is developed by vanillaOVO, a model with 7.2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Supermario V4 perform on standard benchmarks?

Supermario V4 has the following published scores: MMLU 65.41. Compare against reference models on this page or on the LLM Explorer leaderboards.

Supermario V4 by vanillaOVO — VRAM 14.4GB, 32K context

Name: Supermario V4
Author: vanillaOVO

Supermario V4 is an open-source language model by vanillaOVO. Features: 7.2b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.11, Arc: 73.5, HellaSwag: 88.8, MMLU: 65.4, GSM8K: 70.1.

Arxiv:2311.03099 Endpoints compatible Merge Mergekit Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/vanillaOVO/supermario_v4

Supermario V4 Parameters and Internals

Model Type

text generation

Additional Notes

Model is a merge of pre-trained language models.

Input Output

Input Format:

tokenized input (tensors)

Accepted Modalities:

text

Output Format:

decoded text

LLM Name	Supermario V4
Repository 🤗	https://huggingface.co/vanillaOVO/supermario_v4
Model Size	7.2b
Required VRAM	14.4 GB
Updated	2026-07-18
Maintainer	vanillaOVO
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Supermario V4 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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...Web AI HumanAI 012 INSTRUCT XA	512K / 14.4 GB	9	0
...Web AI HumanAI 012 INSTRUCT IA	512K / 14.4 GB	8	0
...Web AI HumanAI 011 INSTRUCT ML	512K / 14.4 GB	7	0
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SpydazWeb HumanAI M2	512K / GB	38	0
...dazWeb AI HumanAI 011 INSTRUCT	512K / 14.4 GB	14	1
SpydazWeb AI HumanAI 009 CHAT	512K / 14.4 GB	6	0
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SpydazWebAI Human AGI 001	512K / 14.4 GB	6	1
...Web AI HumanAI 012 INSTRUCT MX	512K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than vanillaOVO/supermario_v4.