The whisper.cpp project ports OpenAI’s Whisper speech recognition model to C and C++.
Open source
24 alternativeswhisper-ctranslate2
The whisper-ctranslate2 command-line client works with the OpenAI Whisper client and uses CTranslate2.
About whisper-ctranslate2
whisper-ctranslate2 is an open-source command-line client for OpenAI Whisper that runs on the CTranslate2 engine and the Faster-whisper implementation. It keeps the same command-line interface as the original OpenAI Whisper client, so existing commands can be reused. The project states it is up to 4 times faster than openai/whisper at the same accuracy, and up to 16 times faster with batched inference.
It installs as a Python package or as a Docker image that ships with the small, medium and large-v2 models. CPU and GPU execution are handled by CTranslate2, which supports x86-64 and AArch64/ARM64 CPUs; GPU use requires the NVIDIA cuBLAS and cuDNN libraries for CUDA 12 to be installed. Its translate task converts speech into English only.
Key features
- OpenAI Whisper CLI compatibility for easier migration
- Batched inference via --batched and --batch_size options
- Docker image with small, medium and large-v2 models preloaded
- Speaker diarization and Voice Activity Detection filtering
- Loads fine-tuned Whisper models in CTranslate2 format
- Quantization options through --compute_type, including int8 and float16
Best for: Developers and technical users who want faster local Whisper transcription through a familiar command-line interface.
Good for
- Open-source project with a Python package and a prebuilt Docker image
- Runs on CPU and GPU, with automatic selection of the best available hardware
- Accepts custom fine-tuned or quantized models in CTranslate2 format
Watch out for
- The translate task outputs English only, as the sole supported target language
- Batched inference ignores several parameters, including no_speech_threshold and condition_on_previous_text
- GPU execution requires NVIDIA cuBLAS for CUDA 12 and cuDNN 9 for CUDA 12 to be installed
whisper-ctranslate2 at a glance
- Category
- AI & Machine Learning › AI Voice & Audio
- Type
- Open-source project
- Pricing
- Not confirmed. Check the site
- Open source
- Yes · Source code
- Language
- English
- Last checked
- Oct 6, 2026 · Online when checked
- Listed
- Oct 5, 2026
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whisper-ctranslate2 FAQ
How can I install whisper-ctranslate2?
Install the latest stable version with pip install whisper-ctranslate2, or pull the prebuilt Docker image from ghcr.io.
Which languages can the translate task produce?
The translate task converts the source-language transcription to English, which is the only target language supported.
Can I use my own fine-tuned Whisper model?
Yes. The --model_directory option loads a CTranslate2 Whisper model from a directory, such as a quantized version or a fine-tuned model, provided the model is in CTranslate2 format.
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