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openai/whisper-large-v3-turbo

Speech-to-text recipe using the loadable MLX ASR fp16 conversion.

Start this recipeView on Hugging Face
Model metadata
CategoryASRParams0.8BContext448BackendsCUDA, METAL, ROCMTasksASR
Recipe authorship · Recorded configuration verification

Recipe authorship: Curated

Curated and generated describe how this recipe was written, not whether it ran successfully.

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Command builder

Hardware
Variant

mlx-community/whisper-large-v3-turbo-asr-fp16

Mode: Server
Advanced
Features

Estimated memory use

approx

Approximate memory allocation in GB. These estimates are not measured peak usage.

  • Weights: ≈ 1.5 GB
  • KV: ≈ 0.0 GB
  • Drafter: ≈ 0.0 GB
  • Runtime allowance: ≈ 1.0 GB

Estimated to leave ≈ 2.9 GB of the ≈ 5.4 GB available memory.

Next: prepare the executable

Notes

  • This audio runtime must run as a dedicated process and cannot share a server with text generation.
  • This tier is estimated from nearby measurements.

1. Install

Install in your terminal. Uncached model IDs download automatically on first use.

MLXCEL_INSTALL_DIR="${MLXCEL_INSTALL_DIR:-$HOME/.local/share/mlxcel}" \
  && mkdir -p "$MLXCEL_INSTALL_DIR" \
  && curl -fL -o "$MLXCEL_INSTALL_DIR/mlxcel.zip" https://github.com/lablup/mlxcel/releases/download/v0.8.1/mlxcel-macos-aarch64.zip \
  && unzip -o "$MLXCEL_INSTALL_DIR/mlxcel.zip" -d "$MLXCEL_INSTALL_DIR/mlxcel-macos-aarch64" \
  && export PATH="$MLXCEL_INSTALL_DIR/mlxcel-macos-aarch64:$PATH" \
  && mlxcel --version
Installation and download help

Run the install command in your terminal. The selected executable should then be available on PATH. If it is not found, repeat the displayed PATH export in the same terminal.

Model IDs download automatically when first used. The optional download command prepares the checkpoint ahead of time. Uncached models require internet access and enough disk space; gated models also require access approval and credentials.

2. Run

Run this command in the same terminal after preparation. For server modes, keep it running and wait for the listening/ready message. If memory is insufficient, select a smaller checkpoint or reduce context/concurrency in advanced settings.

Copy all includes the selected installation, checkpoint download, and displayed run commands, in that order. Run them in the same shell; multi-node commands belong on their respective machines.

mlxcel serve

This installation provides the full CLI. Use mlxcel serve; select a source build to use the standalone server.

mlxcel serve -m mlx-community/whisper-large-v3-turbo-asr-fp16 --alias whisper-large-v3-turbo
Command flag help
-m
Selects the model or checkpoint repository.
--alias
Sets the served model name used by API clients.

3. Check the first result

For a server, use a second terminal after it is ready. A text chat request returns JSON with choices[0].message.content; specialized endpoints return their task output. Replace sample file paths with your own inputs where shown. Connection refused: check the server address/port and terminal logs. Model access/download errors: check the model ID, permissions, internet connection, and free disk space.

curl http://127.0.0.1:8080/v1/audio/transcriptions \
  -F model=whisper-large-v3-turbo \
  -F "file=@recording.wav"

Performance evidence

No benchmark is recorded for this selected checkpoint and hardware combination. Commands and memory estimates use the catalog's model information.

Memory fit is a model-based estimate, separate from measured throughput and successful inference verification.

No measurement is available for this hardware yet. See the family page for related profiles. Family

Prerequisites

  • Install the mlxcel build for your selected hardware and check the selected checkpoint's memory estimate.
  • Allow internet access and enough disk space to download an uncached checkpoint; obtain Hugging Face access approval when the checkpoint requires it.

Recipe options

  • • Use the ASR fp16 conversion; the plain mlx-community turbo repo lacks the tokenizer and processor files required by mlxcel's STT worker.
  • • The dedicated Whisper worker currently accepts WAV input.

Family

Whisper (encoder-decoder ASR)

ASR

Sibling recipes

pending

Guide

Overview

Whisper Large v3 Turbo transcribes speech into text. This recipe identifies the model as openai/whisper-large-v3-turbo and loads mlx-community/whisper-large-v3-turbo-asr-fp16, which includes the tokenizer and processor files required by mlxcel's Whisper worker.

Prerequisites

Run this recipe in server mode with the Whisper checkpoint as the model. The dedicated speech-to-text worker runs separately from chat generation and accepts WAV input.

Gotchas

Use the ASR fp16 variant specified in the recipe. The plain mlx-community/whisper-large-v3-turbo conversion lacks the full set of ASR files required by mlxcel's audio runtime.

References