Sft Qwen Misaligned V3 Round 2 V2 by obalcells

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Sft Qwen Misaligned V3 Round 2 V2 is an open-source language model by obalcells. Features: 32.8b LLM, VRAM: 131.6GB, Context: 40K, LLM Explorer Score: 0.26.

  Qwen3   Region:us   Safetensors   Sharded   Tensorflow

Sft Qwen Misaligned V3 Round 2 V2 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

Sft Qwen Misaligned V3 Round 2 V2 Parameters and Internals

LLM NameSft Qwen Misaligned V3 Round 2 V2
Repository 🤗https://huggingface.co/obalcells/sft_qwen_misaligned_v3_round_2_v2 
Model Size32.8b
Required VRAM131.6 GB
Updated2026-04-09
Maintainerobalcells
Model Typeqwen3
Model Files  4.5 GB: 1-of-27   4.8 GB: 2-of-27   5.0 GB: 3-of-27   4.8 GB: 4-of-27   5.0 GB: 5-of-27   4.8 GB: 6-of-27   5.0 GB: 7-of-27   4.8 GB: 8-of-27   5.0 GB: 9-of-27   4.8 GB: 10-of-27   5.0 GB: 11-of-27   4.8 GB: 12-of-27   5.0 GB: 13-of-27   4.8 GB: 14-of-27   5.0 GB: 15-of-27   4.8 GB: 16-of-27   5.0 GB: 17-of-27   4.8 GB: 18-of-27   5.0 GB: 19-of-27   4.8 GB: 20-of-27   5.0 GB: 21-of-27   4.8 GB: 22-of-27   5.0 GB: 23-of-27   4.8 GB: 24-of-27   5.0 GB: 25-of-27   4.8 GB: 26-of-27   4.7 GB: 27-of-27
Model ArchitectureQwen3ForCausalLM
Context Length40960
Model Max Length40960
Transformers Version4.57.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

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KAT Dev128K / 65.8 GB27210
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Note: green Score (e.g. "73.2") means that the model is better than obalcells/sft_qwen_misaligned_v3_round_2_v2.

Rank the Sft Qwen Misaligned V3 Round 2 V2 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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Release v20260328a