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Nemotron Terminal 32B by nvidia

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Nemotron Terminal 32B is an open-source language model by nvidia. Features: 32b LLM, VRAM: 65.6GB, Context: 40K, License: other, LLM Explorer Score: 0.31.

  Arxiv:2602.21193   Code-agent   Conversational   En   Endpoints compatible   Eval-results   Nemotron-terminal   Nvidia   Pytorch   Qwen3   Region:us   Safetensors   Sft   Sharded   Tensorflow   Terminal
Model Card on HF 🤗: https://huggingface.co/nvidia/Nemotron-Terminal-32B 

Nemotron Terminal 32B Benchmarks

LLME Score: 0.31395
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Nemotron Terminal 32B (nvidia/Nemotron-Terminal-32B)
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Nemotron Terminal 32B Parameters and Internals

LLM NameNemotron Terminal 32B
Repository 🤗https://huggingface.co/nvidia/Nemotron-Terminal-32B 
Model Size32b
Required VRAM65.6 GB
Updated2026-04-03
Maintainernvidia
Model Typeqwen3
Model Files  4.8 GB: 1-of-14   4.9 GB: 2-of-14   4.9 GB: 3-of-14   5.0 GB: 4-of-14   5.0 GB: 5-of-14   4.8 GB: 6-of-14   4.8 GB: 7-of-14   4.2 GB: 8-of-14   4.8 GB: 9-of-14   5.0 GB: 10-of-14   5.0 GB: 11-of-14   4.8 GB: 12-of-14   4.9 GB: 13-of-14   2.7 GB: 14-of-14
Supported Languagesen
Model ArchitectureQwen3ForCausalLM
Licenseother
Context Length40960
Model Max Length40960
Transformers Version4.57.1
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Errorsreplace

Best Alternatives to Nemotron Terminal 32B

Best Alternatives
Context / RAM
Downloads
Likes
...ll Qwen3 32B Preview7 QAT 200K195K / 65.8 GB93
...ll Qwen3 32B Preview6 QAT 200K195K / 65.8 GB62
...ll Qwen3 32B Preview4 QAT 200K195K / 65.8 GB72
Qwen3 32B40K / 65.6 GB3338661678
Qwen3 32B40K / 65.8 GB1740811
SERA 32B40K / 65.8 GB929110
Qwen3 32B NVFP440K / 20.7 GB14475214
FrogBoss 32B 251040K / 65.8 GB730529
Qwen3 32B FP840K / 34.5 GB21354083
Qwen3 32B Multi Sft 50040K / 65.5 GB1620
Note: green Score (e.g. "73.2") means that the model is better than nvidia/Nemotron-Terminal-32B.

Rank the Nemotron Terminal 32B 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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