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RAI 3.0 R1 VECTOR by Local-Novel-LLM-project

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RAI 3.0 R1 VECTOR is an open-source language model by Local-Novel-LLM-project. Features: 684.5b LLM, VRAM: 184.7GB, Context: 160K, License: apache-2.0, LLM Explorer Score: 0.33.

Base model:quantized:rakuten/r... Base model:rakuten/rakutenai-3...   Conversational   Custom code   Deepseek-r1   Deepseek v3   En   Endpoints compatible   Fp8   Ja   Japanese   Multilingual   Rakutenai   Region:us   Safetensors   Sharded   Task-vector-merging   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Local-Novel-LLM-project/RAI-3.0-R1-VECTOR 

RAI 3.0 R1 VECTOR Benchmarks

LLME Score: 0.33029
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
RAI 3.0 R1 VECTOR (Local-Novel-LLM-project/RAI-3.0-R1-VECTOR)
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RAI 3.0 R1 VECTOR Parameters and Internals

LLM NameRAI 3.0 R1 VECTOR
Repository 🤗https://huggingface.co/Local-Novel-LLM-project/RAI-3.0-R1-VECTOR 
Base Model(s)  DeepSeek R1 0528   Rakuten/RakutenAI-3.0   DeepSeek V3.0324   deepseek-ai/DeepSeek-R1-0528   Rakuten/RakutenAI-3.0   deepseek-ai/DeepSeek-V3-0324
Model Size684.5b
Required VRAM184.7 GB
Updated2026-03-31
MaintainerLocal-Novel-LLM-project
Model Typedeepseek_v3
Model Files  5.2 GB: 1-of-163   4.3 GB: 2-of-163   4.3 GB: 3-of-163   4.3 GB: 4-of-163   4.3 GB: 5-of-163   4.4 GB: 6-of-163   4.3 GB: 7-of-163   4.3 GB: 8-of-163   4.3 GB: 9-of-163   4.3 GB: 10-of-163   4.3 GB: 11-of-163   1.3 GB: 12-of-163   4.3 GB: 13-of-163   4.3 GB: 14-of-163   4.3 GB: 15-of-163   4.3 GB: 16-of-163   4.3 GB: 17-of-163   4.3 GB: 18-of-163   4.3 GB: 19-of-163   4.3 GB: 20-of-163   4.3 GB: 21-of-163   4.3 GB: 22-of-163   4.3 GB: 23-of-163   4.3 GB: 24-of-163   4.3 GB: 25-of-163   4.3 GB: 26-of-163   4.3 GB: 27-of-163   4.3 GB: 28-of-163   4.3 GB: 29-of-163   4.3 GB: 30-of-163   4.3 GB: 31-of-163   4.3 GB: 32-of-163   4.3 GB: 33-of-163   1.8 GB: 34-of-163   4.3 GB: 35-of-163   4.3 GB: 36-of-163   4.3 GB: 37-of-163   4.3 GB: 38-of-163   4.3 GB: 39-of-163   4.3 GB: 40-of-163   4.3 GB: 41-of-163   4.3 GB: 42-of-163   4.3 GB: 43-of-163   4.3 GB: 44-of-163
Supported Languagesja en
Model ArchitectureDeepseekV3ForCausalLM
Licenseapache-2.0
Context Length163840
Model Max Length163840
Transformers Version4.46.3
Vocabulary Size129280
Torch Data Typebfloat16

Best Alternatives to RAI 3.0 R1 VECTOR

Best Alternatives
Context / RAM
Downloads
Likes
DeepSeek R1 0528160K / 180.4 GB10983792403
DeepSeek V3160K / 171.8 GB3110043977
DeepSeek R1160K / 180.4 GB33967912953
DeepSeek V3.0324160K / 184.7 GB3816883094
DeepSeek V3160K / 171.8 GB5213
DeepSeek R1 Zero160K / 180.4 GB3334936
DeepSeek V3.0324 BF16160K / 376 GB775334
DeepSeek R1T Chimera160K / 180.4 GB1152263
DeepSeek V3.1 Terminus160K / 176.1 GB0119
DeepSeek V3.1 Base BF16160K / 358.8 GB4404
Note: green Score (e.g. "73.2") means that the model is better than Local-Novel-LLM-project/RAI-3.0-R1-VECTOR.

Rank the RAI 3.0 R1 VECTOR 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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