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T Pro It 2.0 by t-tech

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T Pro It 2.0 is an open-source language model by t-tech. Features: 32b LLM, VRAM: 65.8GB, Context: 40K, License: apache-2.0, LLM Explorer Score: 0.26.

Base model:finetune:qwen/qwen3...   Base model:qwen/qwen3-32b   Conversational   Endpoints compatible   Qwen3   Region:us   Ru   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/t-tech/T-pro-it-2.0 

T Pro It 2.0 Benchmarks

LLME Score: 0.26034
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
T Pro It 2.0 (t-tech/T-pro-it-2.0)
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T Pro It 2.0 Parameters and Internals

LLM NameT Pro It 2.0
Repository 🤗https://huggingface.co/t-tech/T-pro-it-2.0 
Base Model(s)  Qwen3 32B   Qwen/Qwen3-32B
Model Size32b
Required VRAM65.8 GB
Updated2026-04-23
Maintainert-tech
Model Typeqwen3
Model Files  4.9 GB: 1-of-14   4.9 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   2.1 GB: 14-of-14
Supported Languagesru
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length40960
Model Max Length40960
Transformers Version4.51.3
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151668
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to T Pro It 2.0

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...ll Qwen3 32B Preview7 QAT 200K195K / 65.8 GB33
...ll Qwen3 32B Preview6 QAT 200K195K / 65.8 GB52
...ll Qwen3 32B Preview4 QAT 200K195K / 65.8 GB12
Qwen3 32B40K / 65.6 GB6278531692
Qwen3 32B40K / 65.8 GB644615
Assistant Pepe 32B40K / 65.5 GB34452
Qwen3 32B NVFP440K / 20.7 GB24624117
FrogBoss 32B 251040K / 65.8 GB1210629
Qwen3 32B FP840K / 34.5 GB28799383
Nemotron Terminal 32B40K / 65.6 GB186938
Note: green Score (e.g. "73.2") means that the model is better than t-tech/T-pro-it-2.0.

Rank the T Pro It 2.0 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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