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Mixtral Fusion 4x7B Instruct V0.1 by mmnga

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Mixtral Fusion 4x7B Instruct V0.1 is an open-source language model by mmnga. Features: 24.2b LLM, VRAM: 48.5GB, Context: 32K, License: apache-2.0, MoE, Instruction-Based, LLM Explorer Score: 0.11.

  Conversational   De   En   Es   Fr   Instruct   It   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/mmnga/Mixtral-Fusion-4x7B-Instruct-v0.1 

Mixtral Fusion 4x7B Instruct V0.1 Benchmarks

LLME Score: 0.10736
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral Fusion 4x7B Instruct V0.1 (mmnga/Mixtral-Fusion-4x7B-Instruct-v0.1)
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Mixtral Fusion 4x7B Instruct V0.1 Parameters and Internals

Model Type 
moe
Additional Notes 
This model was constructed by merging experts from another model using a technique called slerp.
Supported Languages 
fr (supported), it (supported), de (supported), es (supported), en (supported)
LLM NameMixtral Fusion 4x7B Instruct V0.1
Repository 🤗https://huggingface.co/mmnga/Mixtral-Fusion-4x7B-Instruct-v0.1 
Model Size24.2b
Required VRAM48.5 GB
Updated2026-05-26
Maintainermmnga
Model Typemixtral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-10   5.0 GB: 2-of-10   5.0 GB: 3-of-10   4.9 GB: 4-of-10   5.0 GB: 5-of-10   5.0 GB: 6-of-10   5.0 GB: 7-of-10   5.0 GB: 8-of-10   5.0 GB: 9-of-10   3.7 GB: 10-of-10
Supported Languagesfr it de es en
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

Quantized Models of the Mixtral Fusion 4x7B Instruct V0.1

Model
Likes
Downloads
VRAM
...Fusion 4x7B Instruct V0.1 GGUF81238 GB
... Fusion 4x7B Instruct V0.1 AWQ2613 GB
...Fusion 4x7B Instruct V0.1 GPTQ21512 GB

Best Alternatives to Mixtral Fusion 4x7B Instruct V0.1

Best Alternatives
Context / RAM
Downloads
Likes
Proto Athena 4x7B32K / 48.4 GB70
Proto Athena V0.2 4x7B32K / 48.4 GB70
...erges MoE 4x7b V10 Mixtralv0.332K / 48.3 GB70
Sixtyoneeighty 4x7B V132K / 48.3 GB660
MixtureofMerges MoE 4x7bRP V1132K / 48.3 GB101
Eclipse Mistral 4x7b32K / 48.5 GB161
West Ramen 7Bx432K / 48.7 GB630
MoE Merging32K / 48.3 GB2680
Boundary Mistral 4x7b MoE32K / 48.7 GB1171
... Extraction 4x7B Instruct V0.132K / 48.5 GB95
Note: green Score (e.g. "73.2") means that the model is better than mmnga/Mixtral-Fusion-4x7B-Instruct-v0.1.

Rank the Mixtral Fusion 4x7B Instruct V0.1 Capabilities

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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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