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FrogBoss 32B 2510 by microsoft

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FrogBoss 32B 2510 is an open-source language model by microsoft. Features: 32b LLM, VRAM: 65.8GB, Context: 40K, License: mit, LLM Explorer Score: 0.33.

  Arxiv:2510.19898 Base model:finetune:qwen/qwen3...   Base model:qwen/qwen3-32b   Conversational   Deploy:azure   Endpoints compatible   Qwen3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/microsoft/FrogBoss-32B-2510 

FrogBoss 32B 2510 Benchmarks

LLME Score: 0.33259
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
FrogBoss 32B 2510 (microsoft/FrogBoss-32B-2510)
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FrogBoss 32B 2510 Parameters and Internals

LLM NameFrogBoss 32B 2510
Repository 🤗https://huggingface.co/microsoft/FrogBoss-32B-2510 
Base Model(s)  Qwen3 32B   Qwen/Qwen3-32B
Model Size32b
Required VRAM65.8 GB
Updated2026-05-02
Maintainermicrosoft
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
Model ArchitectureQwen3ForCausalLM
Licensemit
Context Length40960
Model Max Length40960
Transformers Version4.55.0
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typebfloat16
Errorsreplace

Best Alternatives to FrogBoss 32B 2510

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Context / RAM
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...ll Qwen3 32B Preview7 QAT 200K195K / 65.8 GB43
...ll Qwen3 32B Preview6 QAT 200K195K / 65.8 GB62
...ll Qwen3 32B Preview4 QAT 200K195K / 65.8 GB72
Qwen3 32B40K / 65.8 GB1793914
Qwen3 32B40K / 65.6 GB6278531692
Assistant Pepe 32B40K / 65.5 GB11230
Nemotron Terminal 32B40K / 65.6 GB363237
Qwen3 32B NVFP440K / 20.7 GB14475214
Qwen3 32B FP840K / 34.5 GB28799383
SERA 32B40K / 65.8 GB176112
Note: green Score (e.g. "73.2") means that the model is better than microsoft/FrogBoss-32B-2510.

Rank the FrogBoss 32B 2510 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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