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whisper

A general-purpose speech recognition model by OpenAI that supports multilingual transcription, translation, and language identification.

  • Backend
  • Data
  • AI coding
  • Automation
  • CLI
  • Library/framework
  • Windows
  • macOS
  • Linux
  • Self-hostable
  • Runs locally
Open websiteView on GitHub
whisper screenshot
Popularity
107.8k Stars
GitHub stars
Recent activity
7/28/2026
Updated in the last 30 days
License
MIT
Permissive

Why it matters

We look beyond stars: what problem it solves, whether it creates real utility, and what makes its approach worth noticing.

Last 90 days

Problem

Traditional speech recognition pipelines often require chaining multiple independent models; this project addresses the issue by using a single sequence-to-sequence model for multiple tasks.

Practical value

Provides multiple invocation methods from the command line to Python APIs, supporting multilingual recognition, translation, and language detection with a complete open-source implementation.

Innovation / differentiation

Trained on large-scale weakly supervised data, it uses a unified Transformer architecture with special tokens to jointly represent different speech processing tasks.

Leverage potential

Offers models across different parameter sizes, allowing developers to balance VRAM and speed for local deployment or integration.

Why now

Released during a period of rapid integration between large models and speech technology, meeting developer demand for high-accuracy open-source speech transcription tools.

Community activity

In the last 90 days there were 0 new issues and 32 pull requests; the bounded issue/PR samples include 0 issue authors and 21 PR contributors, with 0 releases.

Maintainer responsiveness

The 0-issue window sample had a — close rate, and the 32-pull-request sample had a 3% merge rate. Maintainer-comment observations covered only — of that issue sample, so response rate and first-response speed are not reported.

21 contributors in PR sample0 releasesPR merge rate 3% · 32 sampled in window

Key highlights

  • Supports multilingual speech transcription and translation
  • Automatic spoken language identification
  • Multiple model sizes ranging from tiny to large

Quick start

How it is installed, how hard it is, and where to start.

Where it runs

Runs locally

Difficulty

Medium — some setup needed

Self-hostableRuns locally
  1. 01Ensure Python 3.8-3.11 and FFmpeg are installed on your system.
  2. 02Install the Whisper package using pip.
  3. 03Run the whisper command in your terminal, specifying the audio file for transcription.
  4. 04Alternatively, call whisper.load_model in your Python script to load the model and execute the transcribe method.

Best for

  • Teams that want data on their own servers
  • Developers who want to try it on their machine

More about it

Whisper is a general-purpose speech recognition system by OpenAI, trained on large-scale weak supervision. It unifies tasks like speech recognition, translation, and language detection into a sequence-to-sequence prediction problem, processing audio directly into text.

The model is available in various sizes, allowing users to choose based on hardware resources (e.g., VRAM) and accuracy requirements. It can be integrated as a Python library or used via a command-line interface to process audio files.

Sources

Each field shows its status and source — expand to review.

15 · Expand

  • capability tags

    Verified

    ai_coding, automation

    Source: admin_cms · cms editor · 8/22/2026

  • editor note

    Verified

    {"en":"This project unifies various speech tasks using a Transformer architecture, suitable for developers needing local speech recognition capabilities. Note that running the model typically requires FFmpeg and sufficient VRAM.","zh":"该项目通过 Transformer 架构统一了多种语音任务，适合需要本地部署语音识别能力的开发者。注意运行该模型通常需要安装 FFmpeg 并具备一定的显存资源。"}

    Source: admin_cms · cms editor · 8/22/2026

  • how to use

    Verified

    {"steps":[{"en":"Ensure Python 3.8-3.11 and FFmpeg are installed on your system.","zh":"确保系统已安装 Python 3.8-3.11 及 FFmpeg。"},{"en":"Install the Whisper package using pip.","zh":"使用 pip 安装 Whisper 软件包。"},{"en":"Run the whisper command in your terminal, specifying the audio file for transcription.","zh":"在命令行运行 whisper 命令并指定音频文件进行转录。"},{"en":"Alternatively, call whisper.load_model in your Python script to load the model and execute the transcribe method.","zh":"或在 Python 脚本中调用 whisper.load_model 加载模型并执行 transcribe 方法。"}],"installAt":"local","difficulty":"medium"}

    Source: admin_cms · cms editor · 8/22/2026

  • intro

    Verified

    {"en":"Whisper is a general-purpose speech recognition system by OpenAI, trained on large-scale weak supervision. It unifies tasks like speech recognition, translation, and language detection into a sequence-to-sequence prediction problem, processing audio directly into text.\n\nThe model is available in various sizes, allowing users to choose based on hardware resources (e.g., VRAM) and accuracy requirements. It can be integrated as a Python library or used via a command-line interface to process audio files.","zh":"Whisper 是 OpenAI 推出的通用语音识别系统，通过大规模弱监督学习训练而成。它将语音识别、翻译和语言检测等任务统一为序列到序列的预测问题，能够直接处理音频流并输出文本。\n\n该模型提供多种规格，用户可根据硬件资源（如 VRAM）和精度需求选择合适的版本。它既可作为 Python 库集成到现有应用中，也支持通过命令行直接处理音频文件。"}

    Source: admin_cms · cms editor · 8/22/2026

  • Latest release

    Verified

    v20250625

    Source: GitHub API · latest_release=v20250625 · 8/22/2026

  • License

    Verified

    MIT

    Source: GitHub API · license.spdx_id=MIT · 8/22/2026

  • needs api key

    Verified

    No

    Source: admin_cms · cms editor · 8/22/2026

  • One-liner

    Verified

    {"en":"A general-purpose speech recognition model by OpenAI that supports multilingual transcription, translation, and language identification.","zh":"OpenAI 开发的通用语音识别模型，支持多语言语音转文字、翻译及语言识别。"}

    Source: admin_cms · cms editor · 8/22/2026

  • Platforms

    Verified

    windows, macos, linux

    Source: admin_cms · cms editor · 8/22/2026

  • Category hint

    Inferred from materials

    developer-tools

    Source: Project README · hint=developer-tools · 8/22/2026

  • product forms

    Verified

    cli, library_framework

    Source: admin_cms · cms editor · 8/22/2026

  • role tags

    Verified

    backend, data

    Source: admin_cms · cms editor · 8/22/2026

  • supports docker

    Verified

    No

    Source: admin_cms · cms editor · 8/22/2026

  • supports local

    Verified

    Yes

    Source: admin_cms · cms editor · 8/22/2026

  • supports self host

    Verified

    Yes

    Source: admin_cms · cms editor · 8/22/2026

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