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Mistral Small Instruct 2409 by unsloth

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Mistral Small Instruct 2409 is an open-source language model by unsloth. Features: 22.2b LLM, VRAM: 44.7GB, Context: 128K, License: other, Instruction-Based, LLM Explorer Score: 0.16.

Base model:finetune:mistralai/... Base model:mistralai/mistral-s...   Instruct   Mistral   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/unsloth/Mistral-Small-Instruct-2409 

Mistral Small Instruct 2409 Benchmarks

LLME Score: 0.16272
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Small Instruct 2409 (unsloth/Mistral-Small-Instruct-2409)
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Mistral Small Instruct 2409 Parameters and Internals

LLM NameMistral Small Instruct 2409
Repository 🤗https://huggingface.co/unsloth/Mistral-Small-Instruct-2409 
Base Model(s)  Mistral Small Instruct 2409   mistralai/Mistral-Small-Instruct-2409
Model Size22.2b
Required VRAM44.7 GB
Updated2026-04-22
Maintainerunsloth
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-9   5.0 GB: 2-of-9   5.0 GB: 3-of-9   4.9 GB: 4-of-9   5.0 GB: 5-of-9   5.0 GB: 6-of-9   4.9 GB: 7-of-9   5.0 GB: 8-of-9   5.0 GB: 9-of-9
Model ArchitectureMistralForCausalLM
Licenseother
Context Length131072
Model Max Length131072
Transformers Version4.44.2
Tokenizer ClassLlamaTokenizer
Padding Token[control_748]
Vocabulary Size32768
Torch Data Typebfloat16

Best Alternatives to Mistral Small Instruct 2409

Best Alternatives
Context / RAM
Downloads
Likes
...lect MistralSmallit MMQA Iter132K / 44.7 GB360
...ct MistralSmallit Mg DPO Iter132K / 60.8 GB380
MS Sunfall V0.7.032K / 44.7 GB312
...istral Small It MMQA DPO Iter132K / 44.7 GB50
...mall Instruct 2409 Abliterated32K / 44.7 GB34
MistralSmall1500CTXDummy32K / 44.7 GB140
MistralSmall1500CTX32K / 44.7 GB130
Note: green Score (e.g. "73.2") means that the model is better than unsloth/Mistral-Small-Instruct-2409.

Rank the Mistral Small Instruct 2409 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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