What are the hardware requirements for InfinityNexus 9B?

InfinityNexus 9B requires approximately 18 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 InfinityNexus 9B and how large is it?

InfinityNexus 9B is developed by ChaoticNeutrals, 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 InfinityNexus 9B perform on standard benchmarks?

InfinityNexus 9B has the following published scores: MMLU 64.49. Compare against reference models on this page or on the LLM Explorer leaderboards.

InfinityNexus 9B by ChaoticNeutrals — VRAM 18GB, 32K context

Name: InfinityNexus 9B
Author: ChaoticNeutrals

InfinityNexus 9B is an open-source language model by ChaoticNeutrals. Features: 7b LLM, VRAM: 18GB, Context: 32K, License: other, Merged, LLM Explorer Score: 0.12, Arc: 68.7, HellaSwag: 86.3, MMLU: 64.5, GSM8K: 56.

Merged Model Base model:endevor/infinityrp-... Base model:jeiku/narrativenexu... En Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ChaoticNeutrals/InfinityNexus_9B

InfinityNexus 9B Parameters and Internals

Additional Notes

This is a merge of pre-trained language models created using mergekit.

Supported Languages

en ()

Training Details

Methodology:

Passthrough merge method

LLM Name	InfinityNexus 9B
Repository 🤗	https://huggingface.co/ChaoticNeutrals/InfinityNexus_9B
Base Model(s)	InfinityRP V1 7B NarrativeNexus 7B Endevor/InfinityRP-v1-7B jeiku/NarrativeNexus_7B
Merged Model	Yes
Model Size	7b
Required VRAM	18 GB
Updated	2026-09-10
Maintainer	ChaoticNeutrals
Model Type	mistral
Model Files	10.0 GB: 1-of-2 8.0 GB: 2-of-2
Supported Languages	en
Model Architecture	MistralForCausalLM
License	other
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the InfinityNexus 9B 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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Note: green Score (e.g. "73.2") means that the model is better than ChaoticNeutrals/InfinityNexus_9B.