What are the hardware requirements for Mergekit Slerp Rayqjvs?

Mergekit Slerp Rayqjvs requires approximately 24.5 GB of VRAM and supports a context window of 1000K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mergekit Slerp Rayqjvs and how large is it?

Mergekit Slerp Rayqjvs is developed by mergekit-community, a model with 12b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate Mergekit Slerp Rayqjvs?

Mergekit Slerp Rayqjvs is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mergekit Slerp Rayqjvs by mergekit-community — VRAM 24.5GB, 1000K context

Name: Mergekit Slerp Rayqjvs
Author: mergekit-community

Mergekit Slerp Rayqjvs is an open-source language model by mergekit-community. Features: 12b LLM, VRAM: 24.5GB, Context: 1000K, Merged, LLM Explorer Score: 0.17.

Merged Model Autotrain compatible Base model:jtatman/mistral nem... Base model:khetterman/abominat... Endpoints compatible Lora Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mergekit-community/mergekit-slerp-rayqjvs

Mergekit Slerp Rayqjvs Parameters and Internals

LLM Name	Mergekit Slerp Rayqjvs
Repository 🤗	https://huggingface.co/mergekit-community/mergekit-slerp-rayqjvs
Base Model(s)	AbominationScience 12B V4 Mergekit Slerp Mirtnuv ... 12b Reasoning Psychology Lora Khetterman/AbominationScience-12B-v4 mergekit-community/mergekit-slerp-mirtnuv jtatman/mistral_nemo_12b_reasoning_psychology_lora
Merged Model	Yes
Model Size	12b
Required VRAM	24.5 GB
Updated	2025-09-18
Maintainer	mergekit-community
Model Type	mistral
Model Files	4.9 GB: 1-of-5 4.9 GB: 2-of-5 4.9 GB: 3-of-5 4.9 GB: 4-of-5 4.9 GB: 5-of-5
Model Architecture	MistralForCausalLM
Context Length	1024000
Model Max Length	1024000
Transformers Version	4.48.2
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072
LoRA Model	Yes
Torch Data Type	bfloat16

Rank the Mergekit Slerp Rayqjvs 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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MN 12B LucidFaun RP RU	1000K / 24.5 GB	1005	6
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Dans SakuraKaze V1.0.0 12B	1000K / 24.5 GB	7	21
...n Eris BMO Violent GRPO V0.420	1000K / 24.5 GB	92	3

Note: green Score (e.g. "73.2") means that the model is better than mergekit-community/mergekit-slerp-rayqjvs.