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Mistral R1 Preview by QuietImpostor

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Mistral R1 Preview is an open-source language model by QuietImpostor. Features: 24b LLM, VRAM: 47.3GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.17.

Base model:finetune:sicariussi... Base model:sicariussicariistuf...   Mistral   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/QuietImpostor/Mistral-R1-Preview 

Mistral R1 Preview Benchmarks

LLME Score: 0.17391
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral R1 Preview (QuietImpostor/Mistral-R1-Preview)
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Mistral R1 Preview Parameters and Internals

LLM NameMistral R1 Preview
Repository 🤗https://huggingface.co/QuietImpostor/Mistral-R1-Preview 
Base Model(s)  Redemption Wind 24B   SicariusSicariiStuff/Redemption_Wind_24B
Model Size24b
Required VRAM47.3 GB
Updated2025-10-31
MaintainerQuietImpostor
Model Typemistral
Model Files  4.8 GB: 1-of-10   4.8 GB: 2-of-10   4.8 GB: 3-of-10   4.9 GB: 4-of-10   4.8 GB: 5-of-10   4.8 GB: 6-of-10   4.9 GB: 7-of-10   4.8 GB: 8-of-10   4.8 GB: 9-of-10   3.9 GB: 10-of-10
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.48.2
Tokenizer ClassLlamaTokenizer
Padding Token<pad>
Vocabulary Size131075
Torch Data Typebfloat16

Best Alternatives to Mistral R1 Preview

Best Alternatives
Context / RAM
Downloads
Likes
...ral Nemo Instruct 24B Merge V11000K / 24.6 GB90
Morax 24B V2128K / 18.3 GB572
Cydonia 24B V4.3128K / 47.3 GB3460102
Sketch Cydonia 24B V1.3128K / 47.3 GB1184
Cogidonia 24B128K / 95.3 GB1491
Neural V1 24B128K / 47.3 GB102
Magidonia 24B V4.3128K / 47.3 GB28662
...donia 24B V4.3 Absolute Heresy128K / 47.1 GB23414
MS3.2 PaintedFantasy V4.1 24B128K / 47.3 GB6413
Sketch Cydonia 24B V1.2128K / 47.3 GB288
Note: green Score (e.g. "73.2") means that the model is better than QuietImpostor/Mistral-R1-Preview.

Rank the Mistral R1 Preview Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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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