What are the hardware requirements for Mixtral 8x7B Instruct V0.1?

Mixtral 8x7B Instruct V0.1 requires approximately 93.6 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 Mixtral 8x7B Instruct V0.1 and how large is it?

Mixtral 8x7B Instruct V0.1 is developed by model-hub, a model with 46.7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Mixtral 8x7B Instruct V0.1 perform on standard benchmarks?

Mixtral 8x7B Instruct V0.1 has the following published scores: LMSYS ELO 1197. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mixtral 8x7B Instruct V0.1 by model-hub — VRAM 93.6GB, 32K context

Name: Mixtral 8x7B Instruct V0.1
Author: model-hub

Mixtral 8x7B Instruct V0.1 is an open-source language model by model-hub. Features: 46.7b LLM, VRAM: 93.6GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.22, ELO: 1197.

Conversational De En Endpoints compatible Es Fr Instruct It Mixtral Moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/model-hub/Mixtral-8x7B-Instruct-v0.1

Mixtral 8x7B Instruct V0.1 Benchmarks

LMSys ELO 1197 vs 1272 (so35) -5.9%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Mixtral 8x7B Instruct V0.1 Parameters and Internals

Model Type

generative, sparse mixture of experts

Additional Notes

Model cannot be instantiated with HF yet.

Supported Languages

fr (Supported), it (Supported), de (Supported), es (Supported), en (Supported)

LLM Name	Mixtral 8x7B Instruct V0.1
Repository 🤗	https://huggingface.co/model-hub/Mixtral-8x7B-Instruct-v0.1
Model Size	46.7b
Required VRAM	93.6 GB
Updated	2026-07-30
Maintainer	model-hub
Model Type	mixtral
Instruction-Based	Yes
Model Files	12.1 GB 12.1 GB 12.1 GB 12.1 GB 12.1 GB 12.1 GB 12.1 GB 12.1 GB 4.9 GB: 1-of-19 5.0 GB: 2-of-19 5.0 GB: 3-of-19 4.9 GB: 4-of-19 5.0 GB: 5-of-19 5.0 GB: 6-of-19 4.9 GB: 7-of-19 5.0 GB: 8-of-19 5.0 GB: 9-of-19 4.9 GB: 10-of-19 5.0 GB: 11-of-19 5.0 GB: 12-of-19 5.0 GB: 13-of-19 4.9 GB: 14-of-19 5.0 GB: 15-of-19 5.0 GB: 16-of-19 4.9 GB: 17-of-19 5.0 GB: 18-of-19 4.2 GB: 19-of-19
Supported Languages	fr it de es en
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mixtral 8x7B Instruct 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 Mixtral 8x7B Instruct V0.1

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x7B Instruct V0.1	32K / 93.6 GB	842893	4720
Mixtral 8x7B Instruct V0.1 FP8	32K / 47.1 GB	3383	0
Merge Mixtral Prometheus 8x7B	32K / 91.9 GB	12	2
...xtral 8x7B Yes Instruct LimaRP	32K / 93.5 GB	5	1
Notux 8x7b V1	32K / 93.6 GB	43	165
BagelMIsteryTour V2 8x7B	32K / 93.5 GB	94	17
...rkrautLM Mixtral 8x7B Instruct	32K / 93.6 GB	84	22
Mixtral 8x7B Instruct V0.1 FP8	32K / 47.1 GB	374	0
Sage Ft Mixtral 8x7b	32K / 90 GB	45	25
Dolphin 2.5 Mixtral 8x7b	32K / 93.6 GB	4125	1235

Note: green Score (e.g. "73.2") means that the model is better than model-hub/Mixtral-8x7B-Instruct-v0.1.