What are the hardware requirements for Zephyr Wizard Kuno Royale BF16 Merge 7B?

Zephyr Wizard Kuno Royale BF16 Merge 7B 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 Zephyr Wizard Kuno Royale BF16 Merge 7B and how large is it?

Zephyr Wizard Kuno Royale BF16 Merge 7B is developed by grimjim, 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 Zephyr Wizard Kuno Royale BF16 Merge 7B perform on standard benchmarks?

Zephyr Wizard Kuno Royale BF16 Merge 7B has the following published scores: MMLU 64.86. Compare against reference models on this page or on the LLM Explorer leaderboards.

Zephyr Wizard Kuno Royale BF16 Merge 7B by grimjim — VRAM 14.5GB, 32K context

Name: Zephyr Wizard Kuno Royale BF16 Merge 7B
Author: grimjim

Zephyr Wizard Kuno Royale BF16 Merge 7B is an open-source language model by grimjim. Features: 7b LLM, VRAM: 14.5GB, Context: 32K, License: cc-by-nc-4.0, Merged, LLM Explorer Score: 0.13, Arc: 68.8, HellaSwag: 86.9, MMLU: 64.9, GSM8K: 63.3.

Merged Model Base model:core-3/kuno-royale-... Base model:grimjim/zephyr-beta... Conversational Endpoints compatible Mistral Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/grimjim/zephyr-wizard-kuno-royale-BF16-merge-7B

Zephyr Wizard Kuno Royale BF16 Merge 7B Parameters and Internals

Model Type

text-generation

Additional Notes

This model was experimentally merged using MergeKit with full weights available at the provided link. It uses the SLERP merge method and combines layers from Zephyr Beta WizardLM 2 and Kuno Royale V2.

LLM Name	Zephyr Wizard Kuno Royale BF16 Merge 7B
Repository 🤗	https://huggingface.co/grimjim/zephyr-wizard-kuno-royale-BF16-merge-7B
Base Model(s)	...ephyr Beta WizardLM 2 Merge 7B Kuno Royale V2 7B grimjim/zephyr-beta-wizardLM-2-merge-7B core-3/kuno-royale-v2-7b
Merged Model	Yes
Model Size	7b
Required VRAM	14.5 GB
Updated	2026-08-04
Maintainer	grimjim
Model Type	mistral
Model Files	5.9 GB: 1-of-3 6.0 GB: 2-of-3 2.6 GB: 3-of-3
Model Architecture	MistralForCausalLM
License	cc-by-nc-4.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.3
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Zephyr Wizard Kuno Royale BF16 Merge 7B 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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MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
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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 grimjim/zephyr-wizard-kuno-royale-BF16-merge-7B.