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Qwen3 4B MegaScience by MegaScience

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Qwen3 4B MegaScience is an open-source language model by MegaScience. Features: 4b LLM, VRAM: 16.1GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.2.

  Arxiv:2507.16812 Base model:finetune:qwen/qwen3...   Base model:qwen/qwen3-4b-base   Conversational Dataset:megascience/megascienc...   En   Endpoints compatible   Qwen3   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/MegaScience/Qwen3-4B-MegaScience 

Qwen3 4B MegaScience Benchmarks

LLME Score: 0.19823
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Qwen3 4B MegaScience (MegaScience/Qwen3-4B-MegaScience)
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Qwen3 4B MegaScience Parameters and Internals

LLM NameQwen3 4B MegaScience
Repository 🤗https://huggingface.co/MegaScience/Qwen3-4B-MegaScience 
Base Model(s)  Qwen3 4B Base   Qwen/Qwen3-4B-Base
Model Size4b
Required VRAM16.1 GB
Updated2026-07-13
MaintainerMegaScience
Model Typeqwen3
Model Files  5.0 GB: 1-of-4   4.9 GB: 2-of-4   5.0 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languagesen
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.52.4
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Torch Data Typefloat32
Errorsreplace

Best Alternatives to Qwen3 4B MegaScience

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FastContext 1.0 4B SFT256K / 8.1 GB5735357
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FastContext 1.0 4B RL256K / 8.1 GB455961
Qwen3 4B Thinking 2507256K / 8.1 GB529167601
Lightning 4B256K / 8.1 GB136
Qwen3 4B Instruct 2507 FP8256K / 5.2 GB99480078
Nexa AI 4B Instruct256K / 8 GB2742
Tac 1256K / 8.1 GB6350
Note: green Score (e.g. "73.2") means that the model is better than MegaScience/Qwen3-4B-MegaScience.

Rank the Qwen3 4B MegaScience 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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