Mixtral 8x7B V0.1 GPTQ is an open-source language model by TheBloke. Features: 46.7b LLM, VRAM: 23.8GB, Context: 32K, License: apache-2.0, MoE, Quantized, HF Score: 65.7, LLM Explorer Score: 0.13, Arc: 65.2, HellaSwag: 84.7, MMLU: 69.4, TruthfulQA: 45.4, WinoGrande: 81.1, GSM8K: 48.3.
Mixtral 8x7B V0.1 GPTQ Benchmarks
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x7B V0.1 GPTQ Parameters and Internals
Model Type
Use Cases
Areas: research, commercial applications
Limitations: No moderation mechanisms as it's a pre-trained base model
Supported Languages fr (fluent), it (fluent), de (fluent), es (fluent), en (fluent)
Training Details
Data Sources: VMware Open Instruct for quantization
Context Length:
Model Architecture: Sparse Mixture of Experts
Input Output
Input Format:
Accepted Modalities:
Output Format:
LLM Name Mixtral 8x7B V0.1 GPTQ Repository 🤗 https://huggingface.co/TheBloke/Mixtral-8x7B-v0.1-GPTQ Model Name Mixtral 8X7B v0.1 Model Creator Mistral AI_ Base Model(s) mistralai/Mixtral-8x7B-v0.1 mistralai/Mixtral-8x7B-v0.1 Model Size 46.7b Required VRAM 23.8 GB Updated 2026-04-21 Maintainer TheBloke Model Type mixtral Model Files 23.8 GB Supported Languages fr it de es en GPTQ Quantization Yes Quantization Type gptq Model Architecture MixtralForCausalLM License apache-2.0 Context Length 32768 Model Max Length 32768 Transformers Version 4.36.0 Tokenizer Class LlamaTokenizer Vocabulary Size 32000 Torch Data Type bfloat16
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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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Release v20260328a