What are the hardware requirements for NeuralSynthesis 7B V0.4 Slerp?

NeuralSynthesis 7B V0.4 Slerp requires approximately 14.5 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 NeuralSynthesis 7B V0.4 Slerp and how large is it?

NeuralSynthesis 7B V0.4 Slerp 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 NeuralSynthesis 7B V0.4 Slerp perform on standard benchmarks?

NeuralSynthesis 7B V0.4 Slerp has the following published scores: MMLU 64.28. Compare against reference models on this page or on the LLM Explorer leaderboards.

NeuralSynthesis 7B V0.4 Slerp by Kukedlc — VRAM 14.5GB, 32K context

Name: NeuralSynthesis 7B V0.4 Slerp
Author: Kukedlc

NeuralSynthesis 7B V0.4 Slerp is an open-source language model by Kukedlc. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.21, Arc: 73.2, HellaSwag: 89.1, MMLU: 64.3, GSM8K: 71.

Merged Model Allknowingroger/multiverseex26... Base model:finetune:kukedlc/ne... Base model:kukedlc/neuralsynth... Endpoints compatible Kukedlc/neuralsynthesis-7b-v0.... Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Kukedlc/NeuralSynthesis-7b-v0.4-slerp

NeuralSynthesis 7B V0.4 Slerp Parameters and Internals

Additional Notes

NeuralSynthesis-7b-v0.4-slerp is a merge of the models allknowingroger/MultiverseEx26-7B-slerp and Kukedlc/NeuralSynthesis-7B-v0.1 using the LazyMergekit tool.

LLM Name	NeuralSynthesis 7B V0.4 Slerp
Repository 🤗	https://huggingface.co/Kukedlc/NeuralSynthesis-7b-v0.4-slerp
Base Model(s)	MultiverseEx26 7B Slerp Kukedlc/NeuralSynthesis-7B-v0.1 allknowingroger/MultiverseEx26-7B-slerp Kukedlc/NeuralSynthesis-7B-v0.1
Merged Model	Yes
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-07-20
Maintainer	Kukedlc
Model Type	mistral
Model Files	9.8 GB: 1-of-2 4.7 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
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the NeuralSynthesis 7B V0.4 Slerp 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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...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
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/NeuralSynthesis-7b-v0.4-slerp.