AssemblyAI vs Deepgram: pricing, features and which to choose

AssemblyAI was founded in late 2017 by machine-learning engineer Dylan Fox after he found existing speech models inaccurate and difficult for developers to use. Its cloud platform serves product and engineering teams through APIs for recorded transcription, real-time speech, speech understanding, guardrails, voice agents, and language-model access. In December 2023, TechCrunch reported that AssemblyAI had raised $50 million in an Accel-led round, bringing total funding to $115 million. The company said its paying customer base had grown 200% year over year to 4,000 brands, while more than 200,000 developers used its platform. AssemblyAI also reported handling roughly 25 million API calls and more than 10 terabytes of data daily.

AssemblyAI’s workflow begins with choosing a product and model, then sending recorded audio through an HTTP request or opening a WebSocket for live transcription. For asynchronous files, developers select Universal-2 at $0.15 per audio hour or Universal-3.5 Pro at $0.21, add options such as speaker diarization, entity detection, or Medical Mode, and receive a transcript after processing. Streaming applications open a session, send audio frames, consume partial and final results, and send a termination message when finished because idle WebSocket time remains billable. Voice applications can connect to the Voice Agent API, provide a system prompt and tools, exchange audio in both directions, and handle turn detection and interruptions. Teams can then pass transcripts to Speech Understanding or the LLM Gateway for structured analysis.

AssemblyAI’s main limitations are cost complexity and developer overhead. Unlike Deepgram and Speechmatics, it bills streaming by open WebSocket duration, so idle time counts; add-ons, multichannel audio, and separate LLM Gateway token charges can also complicate forecasts. Google Cloud Speech-to-Text and AWS Transcribe may suit organizations already committed to those clouds, while AssemblyAI is a standalone API platform rather than a broader cloud suite. Its terms permit use of customer data to maintain, develop, and improve services, including model training, subject to applicable opt-out arrangements, so privacy reviews matter for sensitive workloads. AssemblyAI offers $50 in eligible credits, no monthly minimums, EU speech endpoints at US prices, and a $4.50-per-hour Voice Agent API. Choose it for API-first voice products needing transcription plus speech intelligence; choose competitors for cloud consolidation or simpler procurement.

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.