What are the hardware requirements for Mergekit Slerp Qgjzwtc?

Mergekit Slerp Qgjzwtc requires approximately 24.5 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mergekit Slerp Qgjzwtc and how large is it?

Mergekit Slerp Qgjzwtc 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 Qgjzwtc?

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

Mergekit Slerp Qgjzwtc by mergekit-community — VRAM 24.5GB, 128K context

Name: Mergekit Slerp Qgjzwtc
Author: mergekit-community

Mergekit Slerp Qgjzwtc is an open-source language model by mergekit-community. Features: 12b LLM, VRAM: 24.5GB, Context: 128K, Merged, LLM Explorer Score: 0.17.

Merged Model Base model:hardlyworking/sapph... Base model:readyart/the-omega-... Conversational Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

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

Mergekit Slerp Qgjzwtc Parameters and Internals

LLM Name	Mergekit Slerp Qgjzwtc
Repository 🤗	https://huggingface.co/mergekit-community/mergekit-slerp-qgjzwtc
Base Model(s)	Sapphire 12B ReadyArt/The-Omega-Directive-M-12B-v1.0 hardlyworking/Sapphire-12B ReadyArt/The-Omega-Directive-M-12B-v1.0
Merged Model	Yes
Model Size	12b
Required VRAM	24.5 GB
Updated	2026-06-25
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	131072
Model Max Length	131072
Transformers Version	4.51.1
Tokenizer Class	PreTrainedTokenizer
Padding Token	<pad>
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the Mergekit Slerp Qgjzwtc 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

Best Alternatives to Mergekit Slerp Qgjzwtc

Best Alternatives	Context / RAM	Downloads	Likes
...r Nemo 12B Instruct R 21 09 24	1000K / 24.5 GB	396277	141
MN 12B Mag Mell R1	1000K / 24.5 GB	69558	238
Riverfish Rocinante 12B SFT	1000K / 49.4 GB	166	1
Riverfish Rocinante 12B	1000K / 49.4 GB	111	1
MN 12B LucidFaun RP RU	1000K / 24.5 GB	1005	6
Qliphoth 12B V1.2	1000K / 24.5 GB	107	7
Captain Eris BMO Violent 12B	1000K / 24.5 GB	305	2
Shining Gold Sakura 12B	1000K / 24.5 GB	52	2
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-qgjzwtc.