OpenSonnet Lite by hadadxyz

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OpenSonnet Lite is an open-source language model by hadadxyz. Features: 4b LLM, VRAM: 8.1GB, Context: 256K, License: apache-2.0, LLM Explorer Score: 0.37.

Base model:finetune:qwen/qwen3... Base model:qwen/qwen3-4b-think...   Claude-sonnet   Conversational Dataset:crownelius/opus-4.6-re... Dataset:jackrong/deepseek-v4-d... Dataset:roman1111111/claude-so... Dataset:roman1111111/claude-so... Dataset:roman1111111/gemini-3-... Dataset:roman1111111/gemini-3.... Dataset:teichai/claude-4.5-opu... Dataset:teichai/claude-haiku-4... Dataset:teichai/claude-sonnet-... Dataset:teichai/deepseek-v3.2-... Dataset:teichai/deepseek-v3.2-... Dataset:teichai/lordx64-claude...   Distillation   Distilled   Endpoints compatible   Opensonnet   Peft   Qwen3   Region:us   Safetensors   Sft   Sharded   Sonnet   Tensorflow

OpenSonnet Lite Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

OpenSonnet Lite Parameters and Internals

LLM NameOpenSonnet Lite
Repository 🤗https://huggingface.co/hadadxyz/OpenSonnet-Lite 
Base Model(s)  Qwen3 4B Thinking 2507   Qwen/Qwen3-4B-Thinking-2507
Model Size4b
Required VRAM8.1 GB
Updated2026-05-05
Maintainerhadadxyz
Model Typeqwen3
Model Files  2.0 GB: 1-of-5   2.0 GB: 2-of-5   2.0 GB: 3-of-5   2.0 GB: 4-of-5   0.1 GB: 5-of-5
Model ArchitectureQwen3ForCausalLM
Licenseapache-2.0
Context Length262144
Model Max Length262144
Transformers Version4.56.2
Tokenizer ClassQwen2Tokenizer
Padding Token<|endoftext|>
Vocabulary Size151936
Errorsreplace

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Qwen3 4B Thinking 2507256K / 8.1 GB830285581
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Jan V1 4B256K / 8.1 GB108354353
Qwen3 4B Instruct 2507 FP8256K / 5.2 GB71535873
AgentCPM Explore256K / 8.9 GB204413
Qwen3 4B Thinking 2507 FP8256K / 5.2 GB19253066
Jan Code 4B256K / 8.9 GB42677
Note: green Score (e.g. "73.2") means that the model is better than hadadxyz/OpenSonnet-Lite.

Rank the OpenSonnet Lite 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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Release v20260328a