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H2ogpt Mixtral 8x7b 32K AWQ by h2oai

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H2ogpt Mixtral 8x7b 32K AWQ is an open-source language model by h2oai. Features: 46.7b LLM, VRAM: 24.7GB, Context: 32K, License: apache-2.0, MoE, Quantized, LLM Explorer Score: 0.12.

  4-bit   Awq   Conversational   Endpoints compatible   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/h2oai/h2ogpt-mixtral-8x7b-32k-awq 

H2ogpt Mixtral 8x7b 32K AWQ Benchmarks

LLME Score: 0.11917
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
H2ogpt Mixtral 8x7b 32K AWQ (h2oai/h2ogpt-mixtral-8x7b-32k-awq)
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H2ogpt Mixtral 8x7b 32K AWQ Parameters and Internals

LLM NameH2ogpt Mixtral 8x7b 32K AWQ
Repository 🤗https://huggingface.co/h2oai/h2ogpt-mixtral-8x7b-32k-awq 
Model Size46.7b
Required VRAM24.7 GB
Updated2026-02-07
Maintainerh2oai
Model Typemixtral
Model Files  10.0 GB: 1-of-3   10.0 GB: 2-of-3   4.7 GB: 3-of-3
AWQ QuantizationYes
Quantization Typeawq
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than h2oai/h2ogpt-mixtral-8x7b-32k-awq.

Rank the H2ogpt Mixtral 8x7b 32K AWQ 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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