What are the hardware requirements for Mixtral 11Bx2 MoE 19B?

Mixtral 11Bx2 MoE 19B requires approximately 38.4 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mixtral 11Bx2 MoE 19B and how large is it?

Mixtral 11Bx2 MoE 19B is developed by cloudyu, a model with 19.2b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Mixtral 11Bx2 MoE 19B perform on standard benchmarks?

Mixtral 11Bx2 MoE 19B has the following published scores: MMLU 66.31. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mixtral 11Bx2 MoE 19B by cloudyu — VRAM 38.4GB, 4K context

Name: Mixtral 11Bx2 MoE 19B
Author: cloudyu

Mixtral 11Bx2 MoE 19B is an open-source language model by cloudyu. Features: 19.2b LLM, VRAM: 38.4GB, Context: 4K, License: cc-by-nc-4.0, MoE, LLM Explorer Score: 0.18, Arc: 71.2, HellaSwag: 88.5, MMLU: 66.3, GSM8K: 65.3.

Conversational Endpoints compatible Mixtral Model-index Moe Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/cloudyu/Mixtral_11Bx2_MoE_19B

Mixtral 11Bx2 MoE 19B Benchmarks

ARC: 71.16 vs 96.7 (so35)^-26.4%

HellaSwag: 88.47 vs 95.3 (gpt4)^-7.2%

MMLU: 66.31 vs 88.3 (so35)^-24.9%

GSM8K: 65.28 vs 96.4 (so35)^-32.3%

LLME Score: 0.18262

^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 11Bx2 MoE 19B (cloudyu/Mixtral_11Bx2_MoE_19B)

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Mixtral 11Bx2 MoE 19B Parameters and Internals

Model Type

text-generation

Input Output

Input Format:

Prompt text in accepted format

Accepted Modalities:

text

Output Format:

Generated text

LLM Name	Mixtral 11Bx2 MoE 19B
Repository 🤗	https://huggingface.co/cloudyu/Mixtral_11Bx2_MoE_19B
Model Size	19.2b
Required VRAM	38.4 GB
Updated	2026-04-11
Maintainer	cloudyu
Model Type	mixtral
Model Files	9.9 GB: 1-of-4 10.0 GB: 2-of-4 10.0 GB: 3-of-4 8.5 GB: 4-of-4
Model Architecture	MixtralForCausalLM
License	cc-by-nc-4.0
Context Length	4096
Model Max Length	4096
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Padding Token	<s>
Vocabulary Size	32000
Torch Data Type	float16

Quantized Models of the Mixtral 11Bx2 MoE 19B

Model	Likes	Downloads	VRAM
Mixtral 11Bx2 MoE 19B GGUF	19	1262	6 GB
Mixtral 11Bx2 MoE 19B AWQ	5	13	10 GB
Mixtral 11Bx2 MoE 19B GPTQ	5	11	10 GB

Best Alternatives to Mixtral 11Bx2 MoE 19B

Best Alternatives	Context / RAM	Downloads	Likes
MixTAO 19B Pass	32K / 38.1 GB	3	2
Lorge 2x7B UAMM	32K / 38.2 GB	16	0
Multimerge 19B Pass	32K / 38 GB	10	0
Mistralmath 15B Pass	32K / 38.5 GB	11	0
TaoPassthrough 15B S	32K / 38.4 GB	5	0
Raccoon Small	32K / 38.4 GB	92	1
...oundary Solar Chat 2x10.7B MoE	4K / 38 GB	123	1
SOLAR Math 2x10.7B V0.2	4K / 38.4 GB	305	4
SunnyRain 2x10.7B	4K / 38.4 GB	10	0
19B MATH DPO	4K / 38.4 GB	85	0

Note: green Score (e.g. "73.2") means that the model is better than cloudyu/Mixtral_11Bx2_MoE_19B.

Rank the Mixtral 11Bx2 MoE 19B Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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Mixtral 11Bx2 MoE 19B by cloudyu