Purfview/whisper-standalone-win

Whisper & Faster-Whisper standalone executables for those who don't want to bother with Python.

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Purfview/whisper-standalone-win has 3k+ stars and 150+ forks on GitHub and was last pushed on Nov 7, 2025. Data as of . Signed-in members get hourly updates — create a free account.

Summary Information

Updated 1 hour ago
Type:CLI ToolCategory(s):Voice & Speech AIAI Agents & LLM Apps
Added to GitGenius on September 21st, 2026
Created on February 25th, 2023
Open Issues & Pull Requests: 10 (+0)
GitHub issues: Enabled
Number of forks: 168
Total Stargazers: 3,218 (+0)
Total Subscribers: 59 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 1.0 hours
Mean response time: 3.7 days
90th percentile: 9.5 days
Tracked items: 116

Maintainer activity

2 people did triage or write work on this repository in the last 12 months.

Counts unlabeled, assigned, unassigned, milestoned, demilestoned, locked, unlocked over the last 12 months. These are issue and pull request events that require triage or write permission. Commits and code review are not counted. labeled and renamed are excluded because GitHub issue forms record the issue author as the actor. Figures from October 18, 2026. This count is not comparable across projects: each project's automation decides which of these events a person emits. How this is counted.

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Issue Activity (beta)

Open issues: 11
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 201 days
Stale 30+ days: 9
Stale 90+ days: 7

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • invalid (6)
  • can't reproduce (2)
  • enhancement (2)
  • autism (1)

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Detailed Description

Whisper Standalone Win is a standalone executable distribution of OpenAI's Whisper and Faster-Whisper speech-to-text models for Windows users who want to avoid Python setup and dependency management.

The tool solves the friction of deploying Whisper on Windows by packaging the speech recognition engine as a ready-to-run executable. Rather than requiring users to install Python, manage virtual environments, and resolve dependencies, the project bundles Whisper and Faster-Whisper into self-contained binaries that work immediately after download. This approach eliminates the technical barriers that prevent non-technical users and those unfamiliar with Python tooling from accessing these models.

The project suits Windows users who need speech-to-text transcription without Python expertise or infrastructure. It is particularly valuable for those building standalone applications, batch processing audio files, or integrating transcription into workflows where Python installation is impractical or unwanted. The inclusion of Faster-Whisper alongside standard Whisper gives users a choice between accuracy and speed. The tool also incorporates related capabilities such as speaker diarization, vocal extraction, and subtitle generation, making it useful for more complex audio processing pipelines beyond basic transcription.

Development activity shows consistent maintenance with regular updates addressing user needs and compatibility. The project maintains active engagement with issues and pull requests, indicating responsiveness to problems reported by users. Documentation and build processes receive ongoing attention to ensure the executables remain functional across Windows environments. The maintainer demonstrates commitment to keeping the standalone distribution current with upstream Whisper and Faster-Whisper releases.