What are the hardware requirements for Mistral 2x7b V0.1?

Mistral 2x7b V0.1 requires approximately 25.8 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 Mistral 2x7b V0.1 and how large is it?

Mistral 2x7b V0.1 is developed by HachiML, a model with 12.9b 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 Mistral 2x7b V0.1?

Mistral 2x7b V0.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 2x7b V0.1 by HachiML — VRAM 25.8GB, 32K context

Name: Mistral 2x7b V0.1
Author: HachiML

Mistral 2x7b V0.1 is an open-source language model by HachiML. Features: 12.9b LLM, VRAM: 25.8GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.12.

Base model:merge:mistralai/mis... Base model:merge:nvidia/openma... Base model:mistralai/mistral-7... Base model:nvidia/openmath-mis... Endpoints compatible Instruct Merge Mergekit Mistralai/mistral-7b-instruct-... Mixtral Mixture of experts Moe Nvidia/openmath-mistral-7b-v0.... Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/HachiML/mistral_2x7b_v0.1

Mistral 2x7b V0.1 Parameters and Internals

Model Type

mixture of experts, moe, merge, mergekit

LLM Name	Mistral 2x7b V0.1
Repository 🤗	https://huggingface.co/HachiML/mistral_2x7b_v0.1
Base Model(s)	mistralai/Mistral-7B-Instruct-v0.2 nvidia/OpenMath-Mistral-7B-v0.1-hf mistralai/Mistral-7B-Instruct-v0.2 nvidia/OpenMath-Mistral-7B-v0.1-hf
Model Size	12.9b
Required VRAM	25.8 GB
Updated	2026-07-27
Maintainer	HachiML
Model Type	mixtral
Instruction-Based	Yes
Model Files	10.0 GB: 1-of-3 9.9 GB: 2-of-3 5.9 GB: 3-of-3
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.40.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mistral 2x7b V0.1 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 Mistral 2x7b V0.1

Best Alternatives	Context / RAM	Downloads	Likes
Inf Silent Kunoichi V0.1 2x7B	32K / 25.6 GB	8	0
Inf Silent Kunoichi V0.2 2x7B	32K / 25.6 GB	9	1
NearalMistral 2x7B	32K / 25.8 GB	50	1
Megatron V3 2x7B	32K / 25.8 GB	76	3
MistarlingMaid 2x7B Base	32K / 25.8 GB	52	0
MergedExpert 2x8b	32K / 25.8 GB	5	0
MergedExperts 2x8b	32K / 25.8 GB	6	0
...afted Hermetic Platypus C 2x7B	32K / 25.8 GB	49	0
...tral 7B Instruct V0.2 2x7B MoE	32K / 25.8 GB	1131	4
...tral Instruct MoE Experimental	32K / 25.8 GB	56	2

Note: green Score (e.g. "73.2") means that the model is better than HachiML/mistral_2x7b_v0.1.