What are the hardware requirements for Merged16 Mistral 32?

Merged16 Mistral 32 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 Merged16 Mistral 32 and how large is it?

Merged16 Mistral 32 is developed by Nitish035, a model with 7.2b 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 Merged16 Mistral 32?

Merged16 Mistral 32 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Merged16 Mistral 32 by Nitish035 — VRAM 14.5GB, 32K context

Name: Merged16 Mistral 32
Author: Nitish035

Merged16 Mistral 32 is an open-source language model by Nitish035. Features: 7.2b LLM, VRAM: 14.5GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.19.

Base model:finetune:nitish035/... Base model:nitish035/merged16 ... Conversational En Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/Nitish035/merged16_mistral-32

Merged16 Mistral 32 Parameters and Internals

LLM Name	Merged16 Mistral 32
Repository 🤗	https://huggingface.co/Nitish035/merged16_mistral-32
Base Model(s)	... Mistral 32 Large Grpo 5 Weak3 Nitish035/merged16_mistral_32_large_grpo-5-weak3
Model Size	7.2b
Required VRAM	14.5 GB
Updated	2026-07-19
Maintainer	Nitish035
Model Type	mistral
Model Files	5.0 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.52.4
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32768
Torch Data Type	float16

Rank the Merged16 Mistral 32 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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...Web AI HumanAI 012 INSTRUCT MX	512K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than Nitish035/merged16_mistral-32.