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Kaiju A 57B by lodrick-the-lafted

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Kaiju A 57B is an open-source language model by lodrick-the-lafted. Features: 57b LLM, VRAM: 114.7GB, Context: 195K, License: other, HF Score: 63.6, LLM Explorer Score: 0.12, Arc: 58.8, HellaSwag: 81, MMLU: 72.7, TruthfulQA: 52.3, WinoGrande: 78.8, GSM8K: 38.4.

  Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/lodrick-the-lafted/Kaiju-A-57B 

Kaiju A 57B Benchmarks

ARC: 58.79 vs 96.7 (so35)-39.2%
HellaSwag: 80.95 vs 95.3 (gpt4)-15.1%
MMLU: 72.66 vs 88.3 (so35)-17.7%
TruthfulQA: 52.29 vs 59 (gpt4)-11.4%
WinoGrande: 78.77 vs 87.5 (gpt4)-10%
GSM8K: 38.36 vs 96.4 (so35)-60.2%
LLME Score: 0.12421
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Kaiju A 57B (lodrick-the-lafted/Kaiju-A-57B)
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Kaiju A 57B Parameters and Internals

Model Type 
multimodal
Additional Notes 
Made as an experiment for /r/LocalLlama, merging Tess-M-v1.3 and Tess-M-v1.2 models.
Input Output 
Input Format:
SYSTEM: USER: ASSISTANT:
Accepted Modalities:
text
LLM NameKaiju A 57B
Repository 🤗https://huggingface.co/lodrick-the-lafted/Kaiju-A-57B 
Model Size57b
Required VRAM114.7 GB
Updated2026-04-05
Maintainerlodrick-the-lafted
Model Typellama
Model Files  9.8 GB: 1-of-12   9.8 GB: 2-of-12   9.9 GB: 3-of-12   9.9 GB: 4-of-12   9.8 GB: 5-of-12   9.8 GB: 6-of-12   9.8 GB: 7-of-12   9.8 GB: 8-of-12   9.8 GB: 9-of-12   9.8 GB: 10-of-12   9.9 GB: 11-of-12   6.6 GB: 12-of-12
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length200000
Model Max Length200000
Transformers Version4.35.0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size64002
Torch Data Typefloat16

Best Alternatives to Kaiju A 57B

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DoubleBagel 57B V1.0195K / 114.1 GB31
Kyllene 57B V1.0195K / 113.3 GB257
Note: green Score (e.g. "73.2") means that the model is better than lodrick-the-lafted/Kaiju-A-57B.

Rank the Kaiju A 57B 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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