Kosmox Tiny by wop

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Kosmox Tiny is an open-source language model by wop. Features: LLM, VRAM: 7.6GB, Context: 4K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.14.

  4bit Base model:finetune:unsloth/ph... Base model:unsloth/phi-3-mini-...   Conversational   En   Endpoints compatible   Instruct   Mistral   Pytorch   Quantized   Region:us   Sft   Sharded   Trl   Unsloth
Model Card on HF ๐Ÿค—: https://huggingface.co/wop/kosmox-tiny 

Kosmox Tiny Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Kosmox Tiny (wop/kosmox-tiny)
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Kosmox Tiny Parameters and Internals

Model Type 
text-generation
Additional Notes 
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
Supported Languages 
en (proficient)
LLM NameKosmox Tiny
Repository ๐Ÿค—https://huggingface.co/wop/kosmox-tiny 
Base Model(s)  ...hi 3 Mini 4K Instruct Bnb 4bit   unsloth/Phi-3-mini-4k-instruct-bnb-4bit
Required VRAM7.6 GB
Updated2026-03-27
Maintainerwop
Model Typemistral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-2   2.6 GB: 2-of-2
Supported Languagesen
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length4096
Model Max Length4096
Transformers Version4.41.0
Tokenizer ClassLlamaTokenizer
Padding Token<|placeholder6|>
Vocabulary Size32064
Torch Data Typefloat16

Best Alternatives to Kosmox Tiny

Best Alternatives
Context / RAM
Downloads
Likes
...eZephir Sft Instruct Ead 16bit32K / 14.4 GB560
... Instruct Unsloth Merged 16bit4K / 7.6 GB51
... Mini 4K Instruct Bnb 4bit Ita4K / 7.6 GB11810
... Mini 4K Instruct Bnb 4bit Ita4K / 7.6 GB12110
...ini New Model With Lora Merged4K / 7.6 GB50
Phired4K / 7.6 GB120
Phi3 History V24K / 7.6 GB60
Phi 3 Mini Hospital Topic 504K / 7.6 GB60
Model4K / 7.6 GB50
MainPHI34K / 7.6 GB60
Note: green Score (e.g. "73.2") means that the model is better than wop/kosmox-tiny.

Rank the Kosmox Tiny Capabilities

๐Ÿ†˜ 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! ๐ŸŒŸ

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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Original data from HuggingFace, OpenCompass and various public git repos.
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Release v20260328a