247 lines
8.1 KiB
Markdown
247 lines
8.1 KiB
Markdown
# Provider Comparison Guide
|
|
|
|
This guide helps you choose the right transcription provider for your use case.
|
|
|
|
## Transcription Providers
|
|
|
|
| Provider | Type | Models | Languages | Streaming | Speed | Quality | Cost |
|
|
|----------|------|--------|-----------|-----------|-------|---------|------|
|
|
| **OpenAI** | Cloud | 4 | 57 | Yes | Fast | Excellent | $0.006/min |
|
|
| **Groq** | Cloud | 3 | 57 (1 EN-only) | No | Very Fast | Excellent | Free tier |
|
|
| **Mistral** | Cloud | 2 | 57 | No | Fast | Good | Pay per use |
|
|
| **ElevenLabs** | Cloud | 4 | 57+ | Yes | Fast | Excellent | Pay per use |
|
|
| **Deepgram** | Cloud | 4 | 33-42 | Yes | Very Fast | Excellent | Pay per use |
|
|
| **whisper-cpp** | Local | 12 | 57 (4 EN-only) | No | Varies | Excellent | Free |
|
|
|
|
### OpenAI
|
|
|
|
The original Whisper provider. Reliable and well-documented.
|
|
|
|
**Models:**
|
|
- `whisper-1` - Production speech-to-text (batch)
|
|
- `gpt-4o-transcribe` - High quality with GPT-4o (batch)
|
|
- `gpt-4o-mini-transcribe` - Faster with GPT-4o Mini (batch)
|
|
- `gpt-4o-realtime-preview` - Real-time streaming
|
|
|
|
**Best for:** General use, high accuracy requirements, streaming needs
|
|
|
|
### Groq
|
|
|
|
Extremely fast inference using specialized hardware. OpenAI-compatible API.
|
|
|
|
**Models:**
|
|
- `whisper-large-v3` - Full Whisper v3, best accuracy
|
|
- `whisper-large-v3-turbo` - Faster with slightly lower accuracy
|
|
|
|
**Best for:** Speed-critical applications, English-only use cases, budget-conscious users
|
|
|
|
### Mistral
|
|
|
|
European provider with Voxtral transcription models.
|
|
|
|
**Models:**
|
|
- `voxtral-mini-latest` - Latest Voxtral, recommended
|
|
|
|
**Notes:** Mistral's streaming responses are not real-time audio streaming; hyprvoice treats Voxtral as batch-only.
|
|
|
|
**Best for:** European data residency requirements, Mistral ecosystem users
|
|
|
|
### ElevenLabs
|
|
|
|
Known for voice synthesis, also offers excellent transcription via Scribe.
|
|
|
|
**Models:**
|
|
- `scribe_v1` - 90+ languages, best accuracy (batch)
|
|
- `scribe_v2` - Lower latency (batch)
|
|
- `scribe_v2_realtime` - Streaming-only realtime endpoint
|
|
|
|
**Best for:** Applications needing both TTS and STT, ultra-low latency streaming
|
|
|
|
### Deepgram
|
|
|
|
Streaming-first provider with Nova models. Excellent for real-time applications.
|
|
|
|
**Models:**
|
|
- `flux-general-en` - Streaming with turn detection (English)
|
|
- `nova-3` - Best accuracy, 42 languages
|
|
- `nova-2` - Fast, 33 languages, filler word detection
|
|
|
|
**Notes:** Flux is English-only.
|
|
|
|
**Language Support:** Nova-3 supports 42 languages, Nova-2 supports 33 languages. Not all 57 languages from the master list are available.
|
|
|
|
**Best for:** Real-time transcription, live captions, meeting transcription
|
|
|
|
### whisper-cpp (Local)
|
|
|
|
Run Whisper models locally on your machine. No API keys, no network latency, complete privacy.
|
|
|
|
**Requires:** `whisper-cli` binary installed on your system.
|
|
|
|
**English-only models (faster):**
|
|
| Model | Size | Speed | Quality |
|
|
|-------|------|-------|---------|
|
|
| `tiny.en` | 75MB | Fastest | Basic |
|
|
| `base.en` | 142MB | Fast | Good |
|
|
| `small.en` | 466MB | Medium | Better |
|
|
| `medium.en` | 1.5GB | Slow | Best EN |
|
|
|
|
**Multilingual models:**
|
|
| Model | Size | Speed | Quality |
|
|
|-------|------|-------|---------|
|
|
| `tiny` | 75MB | Fastest | Basic |
|
|
| `base` | 142MB | Fast | Good |
|
|
| `small` | 466MB | Medium | Better |
|
|
| `medium` | 1.5GB | Slow | Great |
|
|
| `large-v1` | 2.9GB | Slowest | Best |
|
|
| `large-v2` | 2.9GB | Slowest | Best |
|
|
| `large-v3` | 3GB | Slowest | Best |
|
|
| `large-v3-turbo` | 1.6GB | Slower | Great |
|
|
|
|
**Best for:** Privacy-sensitive applications, offline use, avoiding API costs
|
|
|
|
---
|
|
|
|
## LLM Providers
|
|
|
|
Used for post-processing transcriptions (formatting, summarization, etc.)
|
|
|
|
| Provider | Models | Quality | Cost |
|
|
|----------|--------|---------|------|
|
|
| **OpenAI** | gpt-4o, gpt-4o-mini | Excellent | Pay per token |
|
|
| **Groq** | llama-3.3-70b, llama-3.1-8b, mixtral-8x7b | Good-Excellent | Free tier |
|
|
|
|
---
|
|
|
|
## Choosing a Provider
|
|
|
|
### Decision Flowchart
|
|
|
|
```
|
|
Need complete privacy?
|
|
├─ Yes → whisper-cpp (local)
|
|
└─ No
|
|
└─ Need real-time streaming?
|
|
├─ Yes
|
|
│ └─ Latency critical (<150ms)?
|
|
│ ├─ Yes → ElevenLabs scribe_v2_realtime (streaming)
|
|
│ └─ No → Deepgram nova-3 or OpenAI realtime
|
|
└─ No (batch)
|
|
└─ Need fastest response?
|
|
├─ Yes → Groq whisper-large-v3-turbo
|
|
└─ No
|
|
└─ Need highest accuracy?
|
|
├─ Yes → OpenAI gpt-4o-transcribe or Groq whisper-large-v3
|
|
└─ No → OpenAI whisper-1 (reliable default)
|
|
```
|
|
|
|
### Quick Recommendations
|
|
|
|
| Use Case | Recommended Provider | Model |
|
|
|----------|---------------------|-------|
|
|
| General dictation | OpenAI | whisper-1 |
|
|
| Fast multilingual | Groq | whisper-large-v3-turbo |
|
|
| Live captions | Deepgram | nova-3 |
|
|
| Ultra-low latency | ElevenLabs | scribe_v2_realtime (streaming) |
|
|
| Offline/privacy | whisper-cpp | base.en or base |
|
|
| High accuracy | OpenAI | gpt-4o-transcribe |
|
|
|
|
---
|
|
|
|
## Language Support
|
|
|
|
All providers support **auto-detect mode** (recommended for most users) which automatically identifies the spoken language.
|
|
|
|
### Full Language Support (57 languages)
|
|
|
|
OpenAI, Groq, Mistral, ElevenLabs, and whisper-cpp multilingual models support all 57 languages:
|
|
|
|
Afrikaans, Arabic, Armenian, Azerbaijani, Belarusian, Bosnian, Bulgarian, Catalan, Chinese, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, Galician, German, Greek, Hebrew, Hindi, Hungarian, Icelandic, Indonesian, Italian, Japanese, Kannada, Kazakh, Korean, Latvian, Lithuanian, Macedonian, Malay, Marathi, Maori, Nepali, Norwegian, Persian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swahili, Swedish, Tagalog, Tamil, Thai, Turkish, Ukrainian, Urdu, Vietnamese, Welsh
|
|
|
|
### English-Only Models
|
|
|
|
These models only support English but are faster:
|
|
|
|
| Provider | Model |
|
|
|----------|-------|
|
|
| whisper-cpp | `tiny.en`, `base.en`, `small.en`, `medium.en` |
|
|
|
|
If you select an English-only model with a non-English language, hyprvoice will:
|
|
1. **At config time:** Show an error and prevent saving
|
|
2. **At runtime:** Fall back to auto-detect with a warning notification
|
|
|
|
### Deepgram Language Support
|
|
|
|
Deepgram Nova models support a subset of languages:
|
|
|
|
**Nova-3 (42 languages):** Arabic, Belarusian, Bosnian, Bulgarian, Catalan, Croatian, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hindi, Hungarian, Indonesian, Italian, Japanese, Kannada, Korean, Latvian, Lithuanian, Macedonian, Malay, Marathi, Norwegian, Polish, Portuguese, Romanian, Russian, Serbian, Slovak, Slovenian, Spanish, Swedish, Tagalog, Tamil, Turkish, Ukrainian, Vietnamese
|
|
|
|
**Nova-2 (33 languages):** Bulgarian, Catalan, Chinese, Czech, Danish, Dutch, English, Estonian, Finnish, French, German, Greek, Hindi, Hungarian, Indonesian, Italian, Japanese, Korean, Latvian, Lithuanian, Malay, Norwegian, Polish, Portuguese, Romanian, Russian, Slovak, Spanish, Swedish, Thai, Turkish, Ukrainian, Vietnamese
|
|
|
|
---
|
|
|
|
## Streaming vs Batch
|
|
|
|
### Batch Transcription
|
|
- Send complete audio file
|
|
- Wait for full transcription
|
|
- Higher accuracy
|
|
- Better for: recordings, file processing, dictation
|
|
|
|
### Streaming Transcription
|
|
- Send audio chunks in real-time
|
|
- Get partial results immediately
|
|
- Lower latency
|
|
- Better for: live captions, voice commands, interactive apps
|
|
|
|
**Streaming providers:** OpenAI (realtime model), ElevenLabs, Deepgram
|
|
|
|
---
|
|
|
|
## Local vs Cloud
|
|
|
|
### Cloud Providers
|
|
|
|
**Pros:**
|
|
- No setup required
|
|
- Always up-to-date models
|
|
- Scales automatically
|
|
- Professional support
|
|
|
|
**Cons:**
|
|
- Requires internet connection
|
|
- API costs
|
|
- Data leaves your machine
|
|
- Potential latency
|
|
|
|
### Local (whisper-cpp)
|
|
|
|
**Pros:**
|
|
- Complete privacy
|
|
- No API costs
|
|
- Works offline
|
|
- No network latency
|
|
- Your data stays on your machine
|
|
|
|
**Cons:**
|
|
- Requires setup (install whisper-cli)
|
|
- Need to download models (75MB-3GB)
|
|
- Uses local CPU/GPU resources
|
|
- Slower on modest hardware
|
|
|
|
### When to Choose Local
|
|
|
|
- Sensitive data (medical, legal, personal)
|
|
- Offline environments
|
|
- High-volume use (avoiding API costs)
|
|
- Privacy-first applications
|
|
- Air-gapped systems
|
|
|
|
### When to Choose Cloud
|
|
|
|
- Quick setup needed
|
|
- Best accuracy required
|
|
- Real-time streaming
|
|
- Light/occasional use
|
|
- Mobile or low-power devices
|