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SauerkrautLM Mixtral 8x7B by VAGOsolutions

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SauerkrautLM Mixtral 8x7B is an open-source language model by VAGOsolutions. Features: 46.7b LLM, VRAM: 93.6GB, Context: 32K, License: apache-2.0, MoE, HF Score: 67.8, LLM Explorer Score: 0.14, Arc: 68.9, HellaSwag: 86, MMLU: 66.7, TruthfulQA: 57.2, WinoGrande: 80.5, GSM8K: 47.5.

  Augmentation   Autotrain compatible   Chatml Dataset:argilla/distilabel-mat...   Dataset:open-orca/slimorca   De   Dpo   En   Endpoints compatible   Es   Finetuned   Fr   German   It   Mistral   Mixtral   Moe   Region:us   Safetensors   Sft   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/VAGOsolutions/SauerkrautLM-Mixtral-8x7B 

SauerkrautLM Mixtral 8x7B Benchmarks

ARC: 68.86 vs 96.7 (so35)-28.8%
HellaSwag: 86.01 vs 95.3 (gpt4)-9.7%
MMLU: 66.69 vs 88.3 (so35)-24.5%
TruthfulQA: 57.2 vs 59 (gpt4)-3.1%
WinoGrande: 80.51 vs 87.5 (gpt4)-8%
GSM8K: 47.54 vs 96.4 (so35)-50.7%
LLME Score: 0.13993
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
SauerkrautLM Mixtral 8x7B (VAGOsolutions/SauerkrautLM-Mixtral-8x7B)
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SauerkrautLM Mixtral 8x7B Parameters and Internals

Model Type 
Mixture of Experts (MoE)
Additional Notes 
Evaluated with lm-evaluation-harness v0.3.0, concerned with data contamination tests showing results below 0.1%. Licensing explains that models may be used for commercial purposes.
Supported Languages 
en (English), de (German), fr (French), it (Italian), es (Spanish)
Training Details 
Data Sources:
Open-Orca/SlimOrca, argilla/distilabel-math-preference-dpo, SauerkrautLM-DPO dataset, Sauerkraut-7b-HerO, HuggingFaceH4/ultrafeedback_binarized
Methodology:
SFT and DPO alignment with German data augmentation
LLM NameSauerkrautLM Mixtral 8x7B
Repository 🤗https://huggingface.co/VAGOsolutions/SauerkrautLM-Mixtral-8x7B 
Model Size46.7b
Required VRAM93.6 GB
Updated2025-09-23
MaintainerVAGOsolutions
Model Typemixtral
Model Files  4.9 GB: 1-of-19   5.0 GB: 2-of-19   5.0 GB: 3-of-19   4.9 GB: 4-of-19   5.0 GB: 5-of-19   5.0 GB: 6-of-19   4.9 GB: 7-of-19   5.0 GB: 8-of-19   5.0 GB: 9-of-19   4.9 GB: 10-of-19   5.0 GB: 11-of-19   5.0 GB: 12-of-19   5.0 GB: 13-of-19   4.9 GB: 14-of-19   5.0 GB: 15-of-19   5.0 GB: 16-of-19   4.9 GB: 17-of-19   5.0 GB: 18-of-19   4.2 GB: 19-of-19
Supported Languagesen de fr it es
Model ArchitectureMixtralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.36.0.dev0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32002
Torch Data Typebfloat16

Quantized Models of the SauerkrautLM Mixtral 8x7B

Model
Likes
Downloads
VRAM
SauerkrautLM Mixtral 8x7B AWQ1627 GB
SauerkrautLM Mixtral 8x7B GGUF919815 GB
SauerkrautLM Mixtral 8x7B AWQ3924 GB
SauerkrautLM Mixtral 8x7B GPTQ21023 GB

Best Alternatives to SauerkrautLM Mixtral 8x7B

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Context / RAM
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Mixtral 8x7B Instruct V0.132K / 93.6 GB4895994657
Nous Hermes 2 Mixtral 8x7B DPO32K / 93.6 GB8997452
Mixtral 8x7B V0.132K / 93.6 GB1173651801
Sensualize Mixtral Bf1632K / 93.6 GB00
Skadi Mixtral V132K / 93.5 GB00
Franziska Mixtral V132K / 93.5 GB00
Typhon Mixtral V132K / 93.4 GB00
GritLM 8x7B KTO32K / 93.6 GB81423
Smaug Mixtral V0.132K / 187.7 GB854812
XLAM 8x7b R32K / 93.6 GB5094415
Note: green Score (e.g. "73.2") means that the model is better than VAGOsolutions/SauerkrautLM-Mixtral-8x7B.

Rank the SauerkrautLM Mixtral 8x7B Capabilities

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Instruction Following and Task Automation  
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