Deepgram vs Speechmatics: pricing, features and which to choose

Deepgram is a San Francisco speech AI company founded in 2015 by Scott Stephenson and Noah Shutty, two physicists who had worked on dark matter detection, and it went through Y Combinator. It builds its own speech models instead of reselling others. In January 2026 it raised a $130 million Series C led by AVP at a $1.3 billion valuation, taking total funding past $215 million, and Stephenson told TechCrunch the company was cash-flow positive the year before. Investors include In-Q-Tel, Madrona, Tiger, Twilio and SAP. Deepgram says more than 1,300 organisations use its models, among them the meeting notetaker Granola, the voice agent platform Vapi and Twilio. Alongside the round it bought OfOne, a Y Combinator startup that builds drive-through ordering agents for quick-service restaurants.

Deepgram offers four API families. Speech-to-text covers pre-recorded files over REST and live audio over WebSockets, with speaker diarization, smart formatting, keyterm prompting for jargon and automatic language detection across 45-plus languages. Text-to-speech, sold under the Aura name, streams spoken replies for agents. The Voice Agent API bundles transcription, a language model and speech into one WebSocket so developers do not have to orchestrate three vendors. Audio Intelligence adds summaries, topic detection, sentiment and intent on top of transcripts. A typical build sends a phone or meeting audio stream to the API and receives word-level timestamps within a few hundred milliseconds. Developers get SDKs for Python, JavaScript, Go and .NET, plus a playground in the console for comparing models on their own audio.

Deepgram is an API for developers, so anyone who wants a finished meeting notetaker or dictation app should look at Otter.ai or similar products built on top of it. Self-serve support is limited to the community and Discord until you sign an enterprise contract. AssemblyAI is the closest rival, with comparable accuracy, strong audio intelligence features and similar per-hour pricing. Speechmatics is stronger on broad language coverage and on-premises deals in Europe, and OpenAI's speech models are convenient for teams already on the OpenAI API. ElevenLabs leads on expressive text-to-speech, where Deepgram's Aura voices are tuned for speed over range. Pick Deepgram when you need low-latency streaming transcription for agents or call analytics at high volume, especially if self-hosting is a requirement.

Speechmatics grew out of research by Tony Robinson, who applied neural networks to speech recognition at Cambridge University in the 1980s, and the company was founded in Cambridge in 2006. Katy Wigdahl is chief executive. In 2022 it raised a $62 million Series B led by Susquehanna Growth Equity, according to TechCrunch. Its stated aim is to understand every voice, and its pitch rests on accuracy for accents, dialects and non-native speakers that trip up other engines. Customers range from broadcasters running live captions to contact centres, legal transcription firms and medical documentation companies. Speechmatics is one of the few speech vendors that has always sold on-premises and on-device deployment alongside its cloud API, which keeps it on shortlists for banks, governments and hospitals with strict data rules.

The product line now covers three jobs. Batch transcription processes recorded audio and video files, with speaker diarization, punctuation, custom dictionaries and translation. Real-time transcription streams live audio for captions and analytics. Agent STT, launched on September 17, 2026, is built for voice agents: it returns transcripts with turn detection, live speaker labels, speaker identification and up to 1,000 custom vocabulary terms over one connection. It plugs into the LiveKit and Pipecat agent frameworks, and Speechmatics says early users integrated it in under an hour. A text-to-speech API, added in June 2026, gives voice agents a matching output voice. Developers use REST and WebSocket APIs with SDKs, or a web portal for one-off files, and add-ons such as summaries and sentiment are priced separately.

Speechmatics' pricing is harder to read than Deepgram's or AssemblyAI's, because the published rates bundle discounts that depend on data sharing and annual commitments. Its text-to-speech is new and has a smaller voice range than ElevenLabs or Cartesia. Deepgram is the closest competitor for voice agents, with Flux turn detection at similar prices and a larger developer community. AssemblyAI is strong on audio intelligence features for recorded calls and meetings. OpenAI's transcription models are convenient for teams already on its API but offer no on-premises option. Pick Speechmatics for accented or code-switched speech, for medical transcription, for live broadcast captioning in many languages, or when audio must stay inside your own data centre. Benchmark it against Deepgram on your own recordings before signing a volume deal.