add docs/providers.md comparison guide
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# Provider Comparison Guide
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This guide helps you choose the right transcription provider for your use case.
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## Transcription Providers
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| Provider | Type | Models | Languages | Streaming | Speed | Quality | Cost |
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|----------|------|--------|-----------|-----------|-------|---------|------|
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| **OpenAI** | Cloud | 4 | 57 | Yes | Fast | Excellent | $0.006/min |
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| **Groq** | Cloud | 3 | 57 (1 EN-only) | No | Very Fast | Excellent | Free tier |
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| **Mistral** | Cloud | 2 | 57 | No | Fast | Good | Pay per use |
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| **ElevenLabs** | Cloud | 4 | 57+ | Yes | Fast | Excellent | Pay per use |
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| **Deepgram** | Cloud | 4 | 33-42 | Yes | Very Fast | Excellent | Pay per use |
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| **whisper-cpp** | Local | 9 | 57 (4 EN-only) | No | Varies | Excellent | Free |
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### OpenAI
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The original Whisper provider. Reliable and well-documented.
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**Models:**
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- `whisper-1` - Production speech-to-text (batch)
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- `gpt-4o-transcribe` - High quality with GPT-4o (batch)
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- `gpt-4o-mini-transcribe` - Faster with GPT-4o Mini (batch)
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- `gpt-4o-realtime-preview` - Real-time streaming
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**Best for:** General use, high accuracy requirements, streaming needs
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### Groq
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Extremely fast inference using specialized hardware. OpenAI-compatible API.
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**Models:**
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- `whisper-large-v3` - Full Whisper v3, best accuracy
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- `whisper-large-v3-turbo` - Faster with slightly lower accuracy
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- `distil-whisper-large-v3-en` - **English only**, fastest option
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**Best for:** Speed-critical applications, English-only use cases, budget-conscious users
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### Mistral
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European provider with Voxtral transcription models.
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**Models:**
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- `voxtral-mini-latest` - Latest Voxtral, recommended
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- `voxtral-mini-2507` - Stable version from July 2025
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**Best for:** European data residency requirements, Mistral ecosystem users
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### ElevenLabs
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Known for voice synthesis, also offers excellent transcription via Scribe.
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**Models:**
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- `scribe_v1` - 90+ languages, best accuracy (batch)
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- `scribe_v2` - Lower latency, real-time optimized (batch)
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- `scribe_v1-streaming` - Real-time transcription
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- `scribe_v2-streaming` - Real-time with <150ms latency
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**Best for:** Applications needing both TTS and STT, ultra-low latency streaming
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### Deepgram
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Streaming-first provider with Nova models. Excellent for real-time applications.
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**Models:**
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- `nova-3` - Best accuracy, 42 languages
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- `nova-3-general` - Same as nova-3
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- `nova-2` - Fast, 33 languages, filler word detection
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- `nova-2-general` - Same as nova-2
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**Language Support:** Nova-3 supports 42 languages, Nova-2 supports 33 languages. Not all 57 languages from the master list are available.
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**Best for:** Real-time transcription, live captions, meeting transcription
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### whisper-cpp (Local)
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Run Whisper models locally on your machine. No API keys, no network latency, complete privacy.
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**Requires:** `whisper-cli` binary installed on your system.
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**English-only models (faster):**
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| Model | Size | Speed | Quality |
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|-------|------|-------|---------|
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| `tiny.en` | 75MB | Fastest | Basic |
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| `base.en` | 142MB | Fast | Good |
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| `small.en` | 466MB | Medium | Better |
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| `medium.en` | 1.5GB | Slow | Best EN |
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**Multilingual models:**
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| Model | Size | Speed | Quality |
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|-------|------|-------|---------|
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| `tiny` | 75MB | Fastest | Basic |
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| `base` | 142MB | Fast | Good |
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| `small` | 466MB | Medium | Better |
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| `medium` | 1.5GB | Slow | Great |
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| `large-v3` | 3GB | Slowest | Best |
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**Best for:** Privacy-sensitive applications, offline use, avoiding API costs
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---
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## LLM Providers
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Used for post-processing transcriptions (formatting, summarization, etc.)
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| Provider | Models | Quality | Cost |
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|----------|--------|---------|------|
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| **OpenAI** | gpt-4o, gpt-4o-mini | Excellent | Pay per token |
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| **Groq** | llama-3.3-70b, llama-3.1-8b, mixtral-8x7b | Good-Excellent | Free tier |
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---
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## Choosing a Provider
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### Decision Flowchart
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```
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Need complete privacy?
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├─ Yes → whisper-cpp (local)
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└─ No
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└─ Need real-time streaming?
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├─ Yes
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│ └─ Latency critical (<150ms)?
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│ ├─ Yes → ElevenLabs scribe_v2-streaming
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│ └─ No → Deepgram nova-3 or OpenAI realtime
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└─ No (batch)
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└─ Need fastest response?
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├─ Yes
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│ └─ English only?
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│ ├─ Yes → Groq distil-whisper-large-v3-en
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│ └─ No → Groq whisper-large-v3-turbo
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└─ No
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└─ Need highest accuracy?
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├─ Yes → OpenAI gpt-4o-transcribe or Groq whisper-large-v3
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└─ No → OpenAI whisper-1 (reliable default)
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```
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### Quick Recommendations
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| Use Case | Recommended Provider | Model |
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|----------|---------------------|-------|
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| General dictation | OpenAI | whisper-1 |
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| Fast English | Groq | distil-whisper-large-v3-en |
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| Fast multilingual | Groq | whisper-large-v3-turbo |
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| Live captions | Deepgram | nova-3 |
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| Ultra-low latency | ElevenLabs | scribe_v2-streaming |
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| Offline/privacy | whisper-cpp | base.en or base |
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| High accuracy | OpenAI | gpt-4o-transcribe |
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---
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## Language Support
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All providers support **auto-detect mode** (recommended for most users) which automatically identifies the spoken language.
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### Full Language Support (57 languages)
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OpenAI, Groq (except distil model), Mistral, ElevenLabs, and whisper-cpp multilingual models support all 57 languages:
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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
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### English-Only Models
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These models only support English but are faster:
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| Provider | Model |
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|----------|-------|
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| Groq | `distil-whisper-large-v3-en` |
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| whisper-cpp | `tiny.en`, `base.en`, `small.en`, `medium.en` |
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If you select an English-only model with a non-English language, hyprvoice will:
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1. **At config time:** Show an error and prevent saving
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2. **At runtime:** Fall back to auto-detect with a warning notification
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### Deepgram Language Support
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Deepgram Nova models support a subset of languages:
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**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
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**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
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---
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## Streaming vs Batch
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### Batch Transcription
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- Send complete audio file
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- Wait for full transcription
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- Higher accuracy
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- Better for: recordings, file processing, dictation
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### Streaming Transcription
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- Send audio chunks in real-time
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- Get partial results immediately
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- Lower latency
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- Better for: live captions, voice commands, interactive apps
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**Streaming providers:** OpenAI (realtime model), ElevenLabs, Deepgram
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---
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## Local vs Cloud
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### Cloud Providers
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**Pros:**
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- No setup required
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- Always up-to-date models
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- Scales automatically
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- Professional support
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**Cons:**
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- Requires internet connection
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- API costs
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- Data leaves your machine
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- Potential latency
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### Local (whisper-cpp)
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**Pros:**
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- Complete privacy
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- No API costs
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- Works offline
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- No network latency
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- Your data stays on your machine
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**Cons:**
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- Requires setup (install whisper-cli)
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- Need to download models (75MB-3GB)
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- Uses local CPU/GPU resources
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- Slower on modest hardware
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### When to Choose Local
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- Sensitive data (medical, legal, personal)
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- Offline environments
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- High-volume use (avoiding API costs)
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- Privacy-first applications
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- Air-gapped systems
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### When to Choose Cloud
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- Quick setup needed
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- Best accuracy required
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- Real-time streaming
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- Light/occasional use
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- Mobile or low-power devices
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@@ -479,4 +479,16 @@ Started: Sun Feb 1 12:22:47 AM CET 2026
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- Updated Development Status table: all items now complete (local, streaming, model mgmt, language validation)
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- Updated Project Structure: added deps/, language/, models/whisper/ packages
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- Updated File Locations: added models directory path
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- Typecheck passes
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### Task 45: Create docs/providers.md comparison guide
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- Created comprehensive provider comparison documentation
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- Transcription providers table: OpenAI, Groq, Mistral, ElevenLabs, Deepgram, whisper-cpp with Type/Models/Languages/Streaming/Speed/Quality/Cost
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- Individual provider sections with models list and "Best for" recommendations
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- LLM providers table: OpenAI and Groq models
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- Decision flowchart for choosing a provider (privacy -> streaming -> speed -> accuracy)
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- Quick recommendations table for common use cases
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- Language support section: full 57-language list, English-only models clearly marked, Deepgram subset languages
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- Streaming vs Batch explanation with use cases
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- Local vs Cloud comparison with pros/cons and when-to-choose guidelines
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- Typecheck passes
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+13
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@@ -1047,19 +1047,19 @@
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"Add '## Streaming vs Batch' section explaining when to use each",
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"Add '## Local vs Cloud' section with tradeoffs (privacy, latency, cost, setup)"
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],
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"verify": [
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"Comparison tables are complete with Language Support column",
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"All providers listed with accurate info",
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"English-only models clearly marked",
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"Language support section is comprehensive",
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"Decision guide is helpful",
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"File is well-formatted markdown",
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"Typecheck passes"
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],
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"passes": false
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},
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{
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"title": "Update docs/config.md with all providers and options",
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"verify": [
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"Comparison tables are complete with Language Support column",
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"All providers listed with accurate info",
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"English-only models clearly marked",
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"Language support section is comprehensive",
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"Decision guide is helpful",
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"File is well-formatted markdown",
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"Typecheck passes"
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],
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"passes": true
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},
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{
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"title": "Update docs/config.md with all providers and options",
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"steps": [
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"Add whisper-cpp provider section with: provider, model, threads options",
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"Add Deepgram provider section with: provider, model, api_key / DEEPGRAM_API_KEY",
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