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Magot V1 Gemma2 8K 9B by grimjim

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Magot V1 Gemma2 8K 9B is an open-source language model by grimjim. Features: 9b LLM, VRAM: 18.6GB, Context: 8K, License: gemma, Merged, LLM Explorer Score: 0.22.

  Merged Model Base model:anthracite-org/magn... Base model:grimjim/kitsunebi-v...   Conversational   Endpoints compatible   Ext 8k   Gemma2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/grimjim/Magot-v1-Gemma2-8k-9B 

Magot V1 Gemma2 8K 9B Benchmarks

MMLU Pro: 37.08
GPQA: 12.86
MUSR: 14.91
BBH: 42.82
IFEval: 29.97 vs 88 (so35)-65.9%
MATH Lvl 5: 9.89
LLME Score: 0.22394
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Magot V1 Gemma2 8K 9B (grimjim/Magot-v1-Gemma2-8k-9B)
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Magot V1 Gemma2 8K 9B Parameters and Internals

Model Type 
text-generation
Additional Notes 
This model is an experiment in using merger as a method of making an Instruct-heavy model less constrained in its text generation. The low weight (0.2) infusion of the Magnum model provided needed variety to text generation. Inherent model safety is still strong due to Instruct base, but narratives are less bounded by positivity. Metadata linkbacks to this model are appreciated when used.
LLM NameMagot V1 Gemma2 8K 9B
Repository 🤗https://huggingface.co/grimjim/Magot-v1-Gemma2-8k-9B 
Base Model(s)  Kitsunebi V1 Gemma2 8K 9B   Magnum V3 9B Customgemma2   grimjim/Kitsunebi-v1-Gemma2-8k-9B   anthracite-org/magnum-v3-9b-customgemma2
Merged ModelYes
Model Size9b
Required VRAM18.6 GB
Updated2026-04-07
Maintainergrimjim
Model Typegemma2
Model Files  1.9 GB: 1-of-10   2.0 GB: 2-of-10   2.0 GB: 3-of-10   2.0 GB: 4-of-10   2.0 GB: 5-of-10   2.0 GB: 6-of-10   2.0 GB: 7-of-10   2.0 GB: 8-of-10   2.0 GB: 9-of-10   0.7 GB: 10-of-10
Context Length8k
Model ArchitectureGemma2ForCausalLM
Licensegemma
Context Length8192
Model Max Length8192
Transformers Version4.44.2
Tokenizer ClassGemmaTokenizer
Padding Token<pad>
Vocabulary Size256000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than grimjim/Magot-v1-Gemma2-8k-9B.

Rank the Magot V1 Gemma2 8K 9B 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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