What are the hardware requirements for Mistroll 7B V2.2?

Mistroll 7B V2.2 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 Mistroll 7B V2.2 and how large is it?

Mistroll 7B V2.2 is developed by BarraHome, 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 Mistroll 7B V2.2 perform on standard benchmarks?

Mistroll 7B V2.2 has the following published scores: MMLU 64.35. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mistroll 7B V2.2 by BarraHome — VRAM 14.4GB, 32K context

Name: Mistroll 7B V2.2
Author: BarraHome

Mistroll 7B V2.2 is an open-source language model by BarraHome. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: mit, Quantized, LLM Explorer Score: 0.13, Arc: 72.8, HellaSwag: 89.2, MMLU: 64.4, GSM8K: 71.2.

Base model:quantized:yam-peleg... Base model:yam-peleg/experimen... Conversational Deploy:azure En Endpoints compatible Es Gguf Mistral Q8 Quantized Region:us Safetensors Sharded Tensorflow Unsloth

Model Card on HF 🤗: https://huggingface.co/BarraHome/Mistroll-7B-v2.2

Mistroll 7B V2.2 Parameters and Internals

LLM Name	Mistroll 7B V2.2
Repository 🤗	https://huggingface.co/BarraHome/Mistroll-7B-v2.2
Base Model(s)	Experiment26 7B yam-peleg/Experiment26-7B
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-08-25
Maintainer	BarraHome
Model Type	mistral
Model Files	7.7 GB 4.9 GB: 1-of-3 5.0 GB: 2-of-3 4.5 GB: 3-of-3
Supported Languages	en es
GGUF Quantization	Yes
Quantization Type	q8\|gguf
Model Architecture	MistralForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.40.0
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mistroll 7B V2.2 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

Quantized Models of the Mistroll 7B V2.2

Model	Likes	Downloads	VRAM
...troll 7B V2.3 NoTsOsm4rt 16bit	0	8	14 GB
...stroll 7B V2.3 NoTsOsm4rt Gguf	0	7	5 GB

Best Alternatives to Mistroll 7B V2.2

Best Alternatives	Context / RAM	Downloads	Likes
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	35	3
MegaBeam Mistral 7B 300K Gguf	282K / 5 GB	34	3
Backrooms Mistral 7B 10e	32K / 14.5 GB	128	0
Mistral 7B Instruct V0.2.gguf	32K / 14.5 GB	17	3
Mistral 7B Instruct V0.2 GGUF	32K / 4.4 GB	26	2
...andle Mistral 7B Instruct V0.2	32K / 14.4 GB	167	0
...andle Dolphin 2.2.1 Mistral 7B	32K / 14.4 GB	96	0
Boptruth Agatha 7B	32K / 14.4 GB	129	0
Mahou 1.2a Mistral 7B	32K / 14.4 GB	33	7
Tamil Mistral 7B Instruct V0.1	32K / 14.8 GB	350	14

Note: green Score (e.g. "73.2") means that the model is better than BarraHome/Mistroll-7B-v2.2.