Advanced speech-to-text and text-to-speech API with industry-leading accuracy, real-time streaming, and support for 30+ languages. Built for developers creating voice applications, call transcription, and conversational AI.
Converts speech to text with incredible accuracy and speed — perfect for transcribing calls, meetings, and voice commands.
Deepgram revolutionizes speech processing with its proprietary deep learning models specifically designed for speech recognition and synthesis. Unlike traditional speech APIs that rely on general-purpose AI, Deepgram's Nova-2 model is purpose-built for audio processing, delivering industry-leading accuracy rates while maintaining sub-300ms latency for real-time applications.\n\nThe platform offers two core services: speech-to-text (STT) and text-to-speech (TTS). The STT API processes both pre-recorded audio files and live audio streams through WebSocket connections, supporting over 30 languages with advanced features like speaker diarization, smart formatting, and custom vocabulary. The Nova-2 model excels at handling challenging audio conditions including accents, background noise, and poor audio quality that often trip up competing services.\n\nFor real-time applications, Deepgram's streaming transcription provides interim results as users speak, enabling natural conversational flows in voice assistants and phone systems. The endpointing feature automatically detects when speakers finish talking, crucial for turn-taking in voice applications. Word-level timestamps and confidence scores help developers build sophisticated voice interfaces.\n\nDeepgram's Aura text-to-speech API generates natural-sounding speech from text with streaming capabilities for real-time voice synthesis. While not as expressively nuanced as premium TTS services like ElevenLabs, Aura offers excellent quality-to-cost ratio for high-volume applications. The combined STT and TTS offering simplifies voice application architecture by providing both directions of speech processing from a single vendor.\n\nKey differentiators include cost-effectiveness (typically 50-75% cheaper than Google Cloud Speech or AWS Transcribe), superior accuracy on difficult audio, and comprehensive developer tools. The platform provides SDKs for Python, JavaScript, Node.js, Go, .NET, and Rust, plus extensive documentation and example implementations for common use cases.\n\nDeepgram integrates seamlessly with voice agent platforms like Vapi, Retell AI, and custom applications. Audio intelligence features extend beyond basic transcription to include summarization, sentiment analysis, topic detection, and intent recognition applied directly to audio streams.\n\nCompared to alternatives, Deepgram offers better accuracy than AssemblyAI for conversational audio, lower latency than Google Speech-to-Text for streaming, and more cost-effective pricing than Azure Speech Services while maintaining enterprise-grade reliability with 99.9% uptime SLAs.
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Deepgram offers the best price-to-performance ratio in speech-to-text with Nova-2's industry-leading accuracy and sub-300ms real-time latency. The combined STT/TTS offering simplifies voice application development, though TTS voice variety is more limited than specialized services.
Deepgram's flagship transcription model is purpose-built for audio rather than adapted from general-purpose AI. It posts the lowest word error rates in independent benchmarks for conversational, accented, and noisy audio, and supports both batch and streaming workloads with speaker diarization, smart formatting, and word-level timestamps.
Launched in 2026, Flux is a conversational speech-to-text model supporting 10 languages — English, Spanish, German, French, Hindi, Russian, Portuguese, Japanese, Italian, and Dutch — with automatic language detection. It includes intelligent endpointing that reliably detects when a speaker has finished, which is essential for natural turn-taking in voice agents.
Instead of orchestrating separate STT, LLM, and TTS providers, Deepgram's Voice Agent API exposes a single endpoint that handles audio in, LLM reasoning, and audio out. This collapses network hops and reduces end-to-end latency, while letting developers plug in business logic and external system calls cleanly.
Beyond transcription, Deepgram applies summarization, sentiment analysis, topic detection, and intent recognition directly to audio streams or files. The same API call that returns the transcript can return structured insights, eliminating the need for a downstream NLP pipeline for common contact-center and analytics use cases.
Enterprise customers can run Deepgram's Nova and TTS models inside their own VPC, on-premises hardware, or air-gapped environments. This is rare among speech APIs and makes Deepgram viable for HIPAA-regulated healthcare, financial services with data-residency requirements, and government workloads where cloud-only providers are blocked.
$0 + $200 credit
From $0.0043/min STT
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Deepgram launched Flux, a multilingual conversational speech-to-text model supporting 10 languages (English, Spanish, German, French, Hindi, Russian, Portuguese, Japanese, Italian, Dutch) with automatic language detection and intelligent endpointing optimized for voice agents. The unified Voice Agent API has been promoted as Deepgram's flagship offering, combining STT, LLM orchestration, and TTS in a single endpoint, alongside a deeper Amazon Connect integration for contact center deployments.
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