🎙�� Speech Recognition

Voxtral-Mini-4B-Realtime-2602

mistralai/Voxtral-Mini-4B-Realtime-2602

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vllm
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Model Details
Full Model IDmistralai/Voxtral-Mini-4B-Realtime-2602
Pipeline / Taskautomatic-speech-recognition
Libraryvllm
Downloads (all-time)1.3M
Likes861
Last Modified3/11/2026
Author / Orgmistralai
PrivateNo � public
⚡ Quick Usage (Python)

Using the 🤗 Transformers library. Install with pip install transformers

from transformers import pipeline

# Load the model
pipe = pipeline("automatic-speech-recognition", model="mistralai/Voxtral-Mini-4B-Realtime-2602")

# Run inference
result = pipe("Your input here")
print(result)
����� Tags
vllmsafetensorsvoxtral_realtimemistral-commonautomatic-speech-recognitionenfresderuzhjaitptnlarhikoarxiv:2602.11298base_model:mistralai/Ministral-3-3B-Base-2512base_model:finetune:mistralai/Ministral-3-3B-Base-2512license:apache-2.0eval-resultsregion:us
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🚀 Use This Model

Access model files, inference API, and full documentation on Hugging Face.

Open on Hugging Face →Browse Model Files ↗�� Browse All Models
🎙�� Task: Speech Recognition

This model is designed for the Speech Recognition task. Explore more models for this use case.

All Speech Recognition Models →
📊 Popularity
Downloads1.3M
����� Community Likes861
🛠�� Requirements
  • Install: pip install vllm
  • Python 3.8+ recommended for Transformers.
  • GPU (CUDA) speeds up inference significantly.
  • Use model.half() for fp16 on limited VRAM.
👋 Need help with code?