What are the hardware requirements for Shadow Clown 7B Slerp?

Shadow Clown 7B Slerp 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 Shadow Clown 7B Slerp and how large is it?

Shadow Clown 7B Slerp is developed by CorticalStack, 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 Shadow Clown 7B Slerp perform on standard benchmarks?

Shadow Clown 7B Slerp has the following published scores: MMLU 64.32. Compare against reference models on this page or on the LLM Explorer leaderboards.

Shadow Clown 7B Slerp by CorticalStack — VRAM 14.4GB, 32K context

Name: Shadow Clown 7B Slerp
Author: CorticalStack

Shadow Clown 7B Slerp is an open-source language model by CorticalStack. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.12, Arc: 73.4, HellaSwag: 89.1, MMLU: 64.3, GSM8K: 70.3.

Merged Model Arxiv:2311.03099 Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow Yam-peleg/experiment26-7b

Model Card on HF 🤗: https://huggingface.co/CorticalStack/shadow-clown-7B-slerp

Shadow Clown 7B Slerp Parameters and Internals

LLM Name	Shadow Clown 7B Slerp
Repository 🤗	https://huggingface.co/CorticalStack/shadow-clown-7B-slerp
Merged Model	Yes
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-25
Maintainer	CorticalStack
Model Type	mistral
Model Files	2.0 GB: 1-of-8 1.9 GB: 2-of-8 2.0 GB: 3-of-8 2.0 GB: 4-of-8 1.9 GB: 5-of-8 1.9 GB: 6-of-8 1.9 GB: 7-of-8 0.8 GB: 8-of-8
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 Shadow Clown 7B 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
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Code Generation
Multi-Language Support and Translation

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...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 CorticalStack/shadow-clown-7B-slerp.