What are the hardware requirements for NeuralKrishna 7B V3?

NeuralKrishna 7B V3 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 NeuralKrishna 7B V3 and how large is it?

NeuralKrishna 7B V3 is developed by Kukedlc, 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 NeuralKrishna 7B V3 perform on standard benchmarks?

NeuralKrishna 7B V3 has the following published scores: MMLU 64.45. Compare against reference models on this page or on the LLM Explorer leaderboards.

NeuralKrishna 7B V3 by Kukedlc — VRAM 14.4GB, 32K context

Name: NeuralKrishna 7B V3
Author: Kukedlc

NeuralKrishna 7B V3 is an open-source language model by Kukedlc. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.12, Arc: 73.6, HellaSwag: 88.9, MMLU: 64.5, GSM8K: 71.

Merged Model Base model:kukedlc/fasciculus-... Base model:kukedlc/neural4gsm8... Base model:kukedlc/neuralglitc... Endpoints compatible Kukedlc/fasciculus-arcuatus-7b... Kukedlc/neural4gsm8k Kukedlc/neuralglitch-yam-peleg... Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Kukedlc/NeuralKrishna-7B-v3

NeuralKrishna 7B V3 Parameters and Internals

Additional Notes

NeuralKrishna-7B-v3 is a merge of the following models using LazyMergekit: * Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT * Kukedlc/Fasciculus-Arcuatus-7B-slerp * Kukedlc/Neural4gsm8k

LLM Name	NeuralKrishna 7B V3
Repository 🤗	https://huggingface.co/Kukedlc/NeuralKrishna-7B-v3
Base Model(s)	Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT Fasciculus Arcuatus 7B Slerp Neural4gsm8k Kukedlc/NeuralGlitch-Yam-Peleg-7B-DT Kukedlc/Fasciculus-Arcuatus-7B-slerp Kukedlc/Neural4gsm8k
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-07-04
Maintainer	Kukedlc
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	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the NeuralKrishna 7B V3 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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...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
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SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than Kukedlc/NeuralKrishna-7B-v3.