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EVA QwQ 32B Preview by win10

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EVA QwQ 32B Preview is an open-source language model by win10. Features: 32b LLM, VRAM: 65.8GB, Context: 32K, Merged, LLM Explorer Score: 0.17.

  Merged Model   Arxiv:2306.01708 Base model:eva-unit-01/eva-qwe... Base model:qwen/qwq-32b-previe...   Conversational   Endpoints compatible   Qwen2   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/win10/EVA-QwQ-32B-Preview 

EVA QwQ 32B Preview Benchmarks

LLME Score: 0.16611
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
EVA QwQ 32B Preview (win10/EVA-QwQ-32B-Preview)
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EVA QwQ 32B Preview Parameters and Internals

LLM NameEVA QwQ 32B Preview
Repository 🤗https://huggingface.co/win10/EVA-QwQ-32B-Preview 
Base Model(s)  QwQ 32B Preview   EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2   Qwen/QwQ-32B-Preview   EVA-UNIT-01/EVA-Qwen2.5-32B-v0.2
Merged ModelYes
Model Size32b
Required VRAM65.8 GB
Updated2026-04-24
Maintainerwin10
Model Typeqwen2
Model Files  5.0 GB: 1-of-14   5.0 GB: 2-of-14   4.9 GB: 3-of-14   4.9 GB: 4-of-14   4.9 GB: 5-of-14   4.9 GB: 6-of-14   4.9 GB: 7-of-14   4.9 GB: 8-of-14   4.9 GB: 9-of-14   4.9 GB: 10-of-14   4.9 GB: 11-of-14   4.9 GB: 12-of-14   4.9 GB: 13-of-14   1.9 GB: 14-of-14
Model ArchitectureQwen2ForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.46.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size152064
Torch Data Typebfloat16
Errorsreplace

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Openbuddy Qwq 32B V24.2 200K195K / 65.8 GB233
Openbuddy Qwq 32B V24.1 200K195K / 65.8 GB123
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...y Qwen2.5coder 32B V24.1q 200K195K / 65.8 GB82
DeepSeek R1 Distill Qwen 32B128K / 65.7 GB10595701546
Qwen2.5 32B128K / 65.5 GB239028174
Baichuan M2 32B128K / 65.8 GB110798120
RomboUltima 32B128K / 20.7 GB306
...wen2.5 32B Inst BaseMerge TIES128K / 65.8 GB6517
OpenReasoning Nemotron 32B128K / 65.8 GB104686123
Note: green Score (e.g. "73.2") means that the model is better than win10/EVA-QwQ-32B-Preview.

Rank the EVA QwQ 32B Preview 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  
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Multi-Language Support and Translation  

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