This post compares five Speech-to-Text (STT) models: Groq Whisper-Large-v3, OpenAI Whisper-1, Deepgram, AssemblyAI, and Google Speech-to-Text (Google STT). It evaluates their features, pros, cons, pricing, API key access, documentation, and multilingual support to assist in selecting the optimal STT solution for various use cases, such as transcription, voice assistants, or multilingual applications.
1. Groq Whisper-Large-v3
Overview: Groq’s implementation of the Whisper-Large-v3 model, optimized for high-speed inference using Groq’s custom hardware. It leverages OpenAI’s open-source Whisper architecture for robust transcription.
Pros:
- High accuracy with low Word Error Rate (WER), competitive with OpenAI Whisper.
- Optimized for speed, offering fast transcription even for large audio files.
- Supports 99 languages, ideal for multilingual applications.
- Cost-effective compared to some cloud-based solutions.
- Suitable for English-only use cases with the Turbo variant for enhanced speed.
Cons:
- Limited to English in the Turbo variant, reducing multilingual flexibility.
- Requires Groq infrastructure, which may limit deployment options compared to open-source Whisper.
- Less mature ecosystem compared to established providers like Deepgram or Google.
- No real-time streaming support, limiting use in live applications.
Pricing:
- Pay-as-you-go: ~$0.0008 per minute of audio (indicative, varies by usage).
- More details: Groq Pricing
API Key Access: Sign up at Groq Console to obtain API keys.
Documentation: Groq API Docs
Multilingual Support: Supports 99 languages, matching OpenAI Whisper’s capabilities. Performs well across diverse accents and noisy environments, but accuracy may drop for less common languages. Ideal for global applications requiring broad language coverage.
2. OpenAI Whisper-1
Overview: OpenAI’s Whisper-1 is part of the Whisper family, an open-source STT model known for robust performance across languages and noisy conditions. Available via OpenAI’s API or self-hosted.
Pros:
- High accuracy with low WER, especially in noisy environments (outperforms Whisper v2/v3 in some benchmarks).
- Supports 99 languages for transcription and translation (non-English to English).
- Open-source availability allows local deployment for privacy-conscious users.
- Strong handling of accents and technical vocabulary.
- Flexible for research and prototyping due to community-driven improvements.
Cons:
- Slower processing speed compared to Deepgram or Groq (40% of video length for large files).
- High computational requirements for large models (1.5B parameters), needing GPUs for efficiency.
- Limited real-time streaming support, less suitable for live applications.
- API pricing can be higher than competitors for high-volume use.
Pricing:
- API: $0.006 per minute of audio.
- Self-hosted: Free (excluding compute costs, e.g., GPU/cloud credits).
- More details: OpenAI Pricing
API Key Access: Register at OpenAI Platform for API keys. For self-hosting, download from GitHub.
Documentation: OpenAI Whisper Docs and GitHub Repo
Multilingual Support: Supports 99 languages with strong performance on major languages (e.g., English, Spanish). Accuracy decreases for low-resource languages. Suitable for transcription and translation, especially for multilingual content creation.
3. Deepgram
Overview: Deepgram’s Nova-3 model is a proprietary STT solution optimized for speed, accuracy, and real-time transcription, with enterprise-grade features.
Pros:
- Industry-leading accuracy with 54.3% WER reduction for streaming and 47.4% for batch compared to competitors.
- Fastest transcription speed (~20s per hour of audio).
- Supports 36+ languages with real-time multilingual transcription.
- Advanced features like diarization, sentiment analysis, and self-serve customization.
- HIPAA-compliant, ideal for healthcare and privacy-sensitive industries.
Cons:
- Higher WER in complex scenarios (e.g., medical jargon) compared to AssemblyAI.
- Limited language support (36+ vs. 99 for Whisper models).
- Credit-based pricing can be confusing for new users.
- Struggles with newly coined terms (e.g., “ChatGPT”).
Pricing:
- Pay-as-you-go: ~$0.0048 per minute of audio.
- Enterprise plans: Custom pricing with discounts.
- $200 free credit for new users.
- More details: Deepgram Pricing
API Key Access: Sign up at Deepgram to access API keys.
Documentation: Deepgram API Docs
Multilingual Support: Supports 36+ languages, with strong performance in English and major languages. Real-time multilingual transcription is a unique feature, but the language count is lower than Whisper or Google STT. Best for applications requiring live transcription in supported languages.
4. AssemblyAI
Overview: AssemblyAI’s Universal-2 model is a leading STT solution, excelling in accuracy and advanced NLP features like summarization and sentiment analysis.
Pros:
- Lowest cumulative WER across diverse scenarios, outperforming most competitors.
- Strong performance in noisy environments and unformatted speech.
- Supports 18+ languages with robust handling of accents and multiple speakers.
- Advanced features like speaker diarization, summarization, and real-time streaming.
- Easy-to-use API with high cosine similarity for accurate transcription.
Cons:
- Struggles with formatted transcription (e.g., punctuation).
- Slower than Deepgram for batch transcription (~30s per hour).
- Pricing can be higher for advanced features like real-time streaming.
- Limited language support compared to Whisper or Google STT.
Pricing:
- Core transcription: $0.00025 per second (~$0.015 per minute).
- Advanced features (e.g., diarization): Additional costs.
- More details: AssemblyAI Pricing
API Key Access: Sign up at AssemblyAI to obtain API keys.
Documentation: AssemblyAI Docs
Multilingual Support: Supports 18+ languages, with strong performance in English and select languages from the Voxpopuli dataset. Less comprehensive than Whisper or Google STT but suitable for applications with moderate multilingual needs.
5. Google Speech-to-Text (Google STT)
Overview: Google STT, part of Google Cloud, offers reliable transcription with extensive language support and integration with Google’s ecosystem.
Pros:
- Supports 120+ languages, among the highest for STT models.
- High audio clarity and robust handling of diverse audio quality.
- Features like speaker diarization, word-level timestamps, and automatic punctuation.
- Seamless integration with Google Cloud services for enterprise users.
- Strong performance with accents and technical vocabulary.
Cons:
- Higher WER in noisy environments compared to Whisper or AssemblyAI.
- Complex setup with permissions and cloud bucket configuration.
- Higher latency for real-time transcription (~500ms).
- Pricing can be costly for high-volume use.
Pricing:
- Standard model: $0.016 per minute.
- Enhanced model: $0.024 per minute.
- More details: Google Cloud STT Pricing
API Key Access: Obtain keys via Google Cloud Console.
Documentation: Google Cloud STT Docs
Multilingual Support: Supports 120+ languages, making it the top choice for applications requiring extensive language coverage. Performs well across major and low-resource languages, ideal for global enterprises and multilingual content.
Multilingual Support Comparison
To identify which STT model supports multiple languages best, we evaluate based on the number of supported languages, accuracy across diverse languages, and suitability for global applications:
- Google STT: Supports 120+ languages, the highest in this comparison. It excels in major and low-resource languages, with robust handling of accents and dialects. Ideal for global enterprises and multilingual content creation.
- Groq Whisper-Large-v3: Supports 99 languages, with strong performance in major languages but reduced accuracy in low-resource ones. The Turbo variant is English-only, limiting its multilingual flexibility. Suitable for broad multilingual applications.
- OpenAI Whisper-1: Supports 99 languages, matching Groq’s Whisper. It handles accents and noisy environments well but may struggle with low-resource languages. Great for transcription and translation in diverse settings.
- Deepgram: Supports 36+ languages, with real-time multilingual transcription as a unique feature. Limited language count compared to Google or Whisper makes it less ideal for extensive multilingual needs. Best for live transcription in supported languages.
- AssemblyAI: Supports 18+ languages, adequate for moderate multilingual needs but significantly less than Google or Whisper. Strong in English and select languages, suitable for targeted multilingual applications.
Best for Multilingual Support: Google STT is the clear leader with 120+ languages, offering unmatched coverage and accuracy for global applications. Groq Whisper-Large-v3 and OpenAI Whisper-1 are strong alternatives for applications needing broad but slightly less extensive language support (99 languages).
Recommendations
- For high-accuracy, multilingual transcription: Google STT for maximum language coverage; Groq Whisper-Large-v3 or OpenAI Whisper-1 for cost-effective, broad multilingual support.
- For real-time, enterprise-grade applications: Deepgram for speed and advanced features; AssemblyAI for accuracy and NLP capabilities.
- For cost-conscious, local deployment: Groq Whisper-Large-v3 for optimized speed; OpenAI Whisper-1 for open-source flexibility.
- For academic or research use: OpenAI Whisper-1 for community-driven improvements and prototyping.
For detailed pricing and feature updates, visit the providers’ websites. Test APIs with real-world data to ensure compatibility and performance for your specific use case.
