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

Mixtral 8x7B 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 V0.1 and how large is it?

Mixtral 8x7B V0.1 is developed by mistralai, 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 V0.1 perform on standard benchmarks?

Mixtral 8x7B V0.1 has the following published scores: MMLU 71.8. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mixtral 8x7B V0.1 by mistralai — VRAM 93.6GB, 32K context

Name: Mixtral 8x7B V0.1
Author: mistralai

Mixtral 8x7B V0.1 is an open-source language model by mistralai. Features: 46.7b LLM, VRAM: 93.6GB, Context: 32K, License: apache-2.0, MoE, HF Score: 65.8, LLM Explorer Score: 0.3, Arc: 92.1, HellaSwag: 81.9, MMLU: 71.8, TruthfulQA: 47.6, WinoGrande: 80.2, GSM8K: 66.

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

Mixtral 8x7B V0.1 Benchmarks

IFEval: 23.26 vs 88 (so35)^-73.6%

ARC: 92.1 vs 96.7 (so35)^-4.8%

HellaSwag: 81.9 vs 95.3 (gpt4)^-14.1%

MMLU: 71.8 vs 88.3 (so35)^-18.7%

TruthfulQA: 47.62 vs 59 (gpt4)^-19.3%

WinoGrande: 80.19 vs 87.5 (gpt4)^-8.4%

GSM8K: 66 vs 96.4 (so35)^-31.5%

OpenCompas: 59.6 vs 73.3 (gpt4)^-18.7%

Exam: 72.7 vs 77.2 (gpt4)^-5.8%

Language: 45.2 vs 62 (gpt4)^-27.1%

Knowledge: 63.2 vs 73.5 (gpt4)^-14%

Understand: 68 vs 70 (gpt4)^-2.9%

Reasoning: 55.9 vs 74.4 (gpt4)^-24.9%

MATH Lvl 5: 9.37

LLME Score: 0.29733

^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 V0.1 (mistralai/Mixtral-8x7B-v0.1)

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Mixtral 8x7B V0.1 Parameters and Internals

Model Type

generative, Sparse Mixture of Experts

Additional Notes

Mixtral-8x7B is a pretrained base model and therefore does not have any moderation mechanisms.

Supported Languages

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

LLM Name	Mixtral 8x7B V0.1
Repository 🤗	https://huggingface.co/mistralai/Mixtral-8x7B-v0.1
Model Size	46.7b
Required VRAM	93.6 GB
Updated	2026-04-27
Maintainer	mistralai
Model Type	mixtral
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

Quantized Models of the Mixtral 8x7B V0.1

Model	Likes	Downloads	VRAM
Mixtral 8x7B V0.1 GGUF	437	5842	15 GB
...hon Mixtral V1.3.75bpw H6 EXL2	3	1	22 GB
Mixtral 8x7B V0.1 GPTQ	127	91	23 GB
Mixtral 8x7b V0.1 AWQ	11	2718	24 GB
... 8x7B DPO 5.0bpw H6 EXL2 Rpcal	1	6	29 GB
... 8x7B DPO 3.7bpw H6 EXL2 Rpcal	4	5	21 GB
... 8x7B DPO 6.0bpw H6 EXL2 Rpcal	1	6	35 GB
Mixtral 8x7B V0.1 GGUF	1	248	17 GB
...Hermes 2 Mixtral 8x7B DPO 4bit	18	302	10 GB
...ixtral 8x7B DPO 5.0bpw H6 EXL2	6	5	29 GB

Best Alternatives to Mixtral 8x7B V0.1

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x7B Instruct V0.1	32K / 93.6 GB	636216	4670
Nous Hermes 2 Mixtral 8x7B DPO	32K / 93.6 GB	8718	453
Sensualize Mixtral Bf16	32K / 93.6 GB	0	0
Skadi Mixtral V1	32K / 93.5 GB	0	0
Franziska Mixtral V1	32K / 93.5 GB	0	0
Typhon Mixtral V1	32K / 93.4 GB	0	0
GritLM 8x7B KTO	32K / 93.6 GB	8142	3
Smaug Mixtral V0.1	32K / 187.7 GB	8548	12
Mixtral 8x7B Instruct V0.1 FP8	32K / 47.1 GB	5017	0
XLAM 8x7b R	32K / 93.6 GB	50944	15

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

Rank the Mixtral 8x7B V0.1 Capabilities

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Instruction Following and Task Automation
Factuality and Completeness of Knowledge
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Mixtral 8x7B V0.1 by mistralai