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Mixtral GQA 400M V2 by BEE-spoke-data

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  Autotrain compatible   Conversational   En   Endpoints compatible   Mixtral   Region:us   Safetensors
Model Card on HF 🤗: https://huggingface.co/BEE-spoke-data/Mixtral-GQA-400m-v2 

Mixtral GQA 400M V2 Benchmarks

ARC: 20.22 vs 96.7 (so35)-79.1%
HellaSwag: 27.78 vs 95.3 (gpt4)-70.8%
MMLU: 26.1 vs 88.3 (so35)-70.4%
TruthfulQA: 46.55 vs 59 (gpt4)-21.1%
WinoGrande: 49.96 vs 87.5 (gpt4)-42.9%
GSM8K: 0.08 vs 96.4 (so35)-99.9%
LLME Score: 0.19382
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral GQA 400M V2 (BEE-spoke-data/Mixtral-GQA-400m-v2)
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Mixtral GQA 400M V2 Parameters and Internals

Model Type 
text-generation
Supported Languages 
en (full)
LLM NameMixtral GQA 400M V2
Repository 🤗https://huggingface.co/BEE-spoke-data/Mixtral-GQA-400m-v2 
Model Size400m
Required VRAM4.3 GB
Updated2025-09-16
MaintainerBEE-spoke-data
Model Typemixtral
Model Files  4.3 GB   0.0 GB
Supported Languagesen
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.37.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat32

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Rank the Mixtral GQA 400M V2 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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