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OpenSeeker V2 30B SFT by PolarSeeker

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OpenSeeker V2 30B SFT is an open-source language model by PolarSeeker. Features: 30b LLM, VRAM: 61.3GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.31.

  Arxiv:2605.04036   Conversational   Deep-research   Endpoints compatible   Qwen3   Qwen3 moe   React   Region:us   Safetensors   Search-agent   Sharded   Tensorflow   Tool-use
Model Card on HF 🤗: https://huggingface.co/PolarSeeker/OpenSeeker-v2-30B-SFT 

OpenSeeker V2 30B SFT Benchmarks

LLME Score: 0.30733
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
OpenSeeker V2 30B SFT (PolarSeeker/OpenSeeker-v2-30B-SFT)
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OpenSeeker V2 30B SFT Parameters and Internals

LLM NameOpenSeeker V2 30B SFT
Repository 🤗https://huggingface.co/PolarSeeker/OpenSeeker-v2-30B-SFT 
Model Size30b
Required VRAM61.3 GB
Updated2026-05-06
MaintainerPolarSeeker
Model Typeqwen3_moe
Model Files  5.4 GB: 0-of-12   5.4 GB: 1-of-12   5.4 GB: 2-of-12   5.4 GB: 3-of-12   5.4 GB: 4-of-12   5.4 GB: 5-of-12   5.4 GB: 6-of-12   5.4 GB: 7-of-12   5.4 GB: 8-of-12   5.4 GB: 9-of-12   5.3 GB: 10-of-12   2.0 GB: 11-of-12
Model ArchitectureQwen3MoeForCausalLM
Licenseapache-2.0
Context Length262144
Model Max Length262144
Transformers Version4.51.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to OpenSeeker V2 30B SFT

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Qwen3 30B A3B YOYO V2986K / 61.1 GB245
Qwen3 Coder 30B A3B Instruct256K / 61.1 GB24066631019
Qwen3 30B A3B Instruct 2507256K / 61.1 GB1131278805
Qwen3 30B A3B Instruct 2507256K / 61.1 GB294513
Lynx Instruct 30B256K / 61.1 GB3604553
Note: green Score (e.g. "73.2") means that the model is better than PolarSeeker/OpenSeeker-v2-30B-SFT.

Rank the OpenSeeker V2 30B SFT 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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