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Mixtral 8x7B Instruct V0.1 Hf 2bit G16 S128 HQQ by mobiuslabsgmbh

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Mixtral 8x7B Instruct V0.1 Hf 2bit G16 S128 HQQ is an open-source language model by mobiuslabsgmbh. Features: LLM, VRAM: 18GB, Context: 32K, License: apache-2.0, MoE, Quantized, Instruction-Based, LLM Explorer Score: 0.11.

  2bit   Conversational   Instruct   Mixtral   Moe   Quantized   Region:us
Model Card on HF 🤗: https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-2bit_g16_s128-HQQ 

Mixtral 8x7B Instruct V0.1 Hf 2bit G16 S128 HQQ Benchmarks

LLME Score: 0.10582
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mixtral 8x7B Instruct V0.1 Hf 2bit G16 S128 HQQ (mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-2bit_g16_s128-HQQ)
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Mixtral 8x7B Instruct V0.1 Hf 2bit G16 S128 HQQ Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model uses Half-Quadratic Quantization (HQQ) for 2-bit quantization.
Input Output 
Accepted Modalities:
text
LLM NameMixtral 8x7B Instruct V0.1 Hf 2bit G16 S128 HQQ
Repository 🤗https://huggingface.co/mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-2bit_g16_s128-HQQ 
Required VRAM18 GB
Updated2026-05-18
Maintainermobiuslabsgmbh
Model Typemixtral
Instruction-BasedYes
Model Files  18.0 GB
Quantization Type2bit
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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...eryTour V2 8x7B 4.5bpw H6 EXL232K / 26.5 GB92
... 4bit MoE 3bit Metaoffload HQQ32K / 22.4 GB5613
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Note: green Score (e.g. "73.2") means that the model is better than mobiuslabsgmbh/Mixtral-8x7B-Instruct-v0.1-hf-2bit_g16_s128-HQQ.

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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