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unslothai/whisper-tiny-GGUF overview

Whisper Tiny F16 for Unsloth Studio Run fast, fully local speech to text dictation in Unsloth Studio https://unsloth.ai/docs . Whisper Tiny has the lowest down…

whisper.cppwhisperggmlf16unsloth-studiounslothautomatic-speech-recognitionbase_model:unslothai/whisper-tinybase_model:finetune:unslothai/whisper-tinylicense:apache-2.0region:us
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automatic-speech-recognition
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Model Details

Model IDunslothai/whisper-tiny-GGUF
Authorunslothai
Pipelineautomatic-speech-recognition
Licenseapache-2.0
Base modelunslothai/whisper-tiny
Last modified2026-07-17T08:18:33.000Z

Model README

---

base_model: unslothai/whisper-tiny

license: apache-2.0

library_name: whisper.cpp

pipeline_tag: automatic-speech-recognition

tags:

  • whisper
  • whisper.cpp
  • ggml
  • f16
  • unsloth-studio
  • unsloth

---

Whisper Tiny F16 for Unsloth Studio

Run fast, fully local speech-to-text dictation in Unsloth Studio. Whisper Tiny has the lowest download size and memory use in the default Whisper lineup, making it the fastest option for short everyday dictation.

Run in Unsloth Studio

  1. Install or update Unsloth Studio.
  2. Open Settings > Voice.
  3. Open the local dictation model picker and select Whisper Tiny.
  4. Let Studio download and cache the model.
  5. Use the microphone button in the chat composer to dictate locally.

The model runs on your device through whisper.cpp. Your recorded audio does not need to be sent to a hosted transcription service.

Model file

  • whisper-tiny.bin: native F16 model for whisper.cpp
  • Download size: approximately 78 MB
  • Best for: fastest startup, lowest memory use, and short dictation

whisper.cpp uses a custom GGML binary format for Whisper. The model file is therefore named .bin, not .gguf, even though this repository follows the common -GGUF repository naming convention.

No low-bit quantization was applied. Matrix weights are stored as F16, while tensors that whisper.cpp requires in F32 remain F32.

Manual whisper.cpp usage

whisper-cli -m whisper-tiny.bin -f audio.wav

Integrity

  • Source model.safetensors SHA-256: 7ebd0e69e78190ffe1438491fa05cc1f5c1aa3a4c4db3bc1723adbb551ea2395
  • Converted model SHA-256: bf4711d269a0c0bc7d8411fc2d78d4c6727a215406da46c42975e15684b01746
  • Conversion tool: ggml-org/whisper.cpp commit 080bbbe85230f624f0b52127f1ae1218247989f9

The converted model was loaded by whisper.cpp and passed an end-to-end transcription test.

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