AssemblyAI Alternatives: 9 Speech-to-Text APIs Compared

The best AssemblyAI alternative depends on which part of AssemblyAI you're replacing. For real-time voice agents, Deepgram is the closest competitor. For audio where speakers switch languages, look at Gladia or ElevenLabs Scribe. For audio that can't leave your servers without a large contract, look at Speechmatics, Azure Speech containers or self-hosted Whisper. If your company already runs on one cloud, Google Cloud Speech-to-Text or Azure Speech keeps everything on one bill. And if you want no per-hour fee at all, run faster-whisper on your own GPUs.

That framing matters because AssemblyAI is no longer just a transcription API. It now sells pre-recorded and streaming speech-to-text, a Dictation API, text-to-speech, PII redaction, and an LLM Gateway for summaries and analysis. Most alternatives match one or two of those pieces, not all of them.

Here's how the main options line up.

Quick Comparison

What You're Comparing Against

AssemblyAI's models page sets the bar. For recorded audio it recommends Universal-3.5 Pro, which covers 18 languages with native code switching, contextual prompting, and keyterm lists of up to 1,000 words. Anything outside those 18 languages falls back to Universal-2, for 99 languages in total.

For streaming, Universal-3.6 Pro Realtime covers 32 languages with code switching, and AssemblyAI lists it at sub-300ms latency. Medical Mode and a beta Veterinary Mode are add-ons that fix drug names and clinical terms.

Around the models, AssemblyAI has built a bundle:

• Guardrails: PII redaction and content moderation on transcripts.
• LLM Gateway: one OpenAI-compatible API to 25+ models from Claude, GPT, Gemini and others, plus a speech understanding endpoint that translates, summarizes, formats or identifies speakers.
• Dictation API: send an utterance, get back cleaned-up text alongside the verbatim transcript.
• AssemblyAI-TTS-1: text-to-speech, so a voice agent can run on one API key.

On the pricing page, speech-to-text is billed per hour of audio, and features like keyterms, diarization and Medical Mode are priced as separate add-ons.

So why do teams look around? Usually for one of these reasons:

• Self-hosting is a big commitment. AssemblyAI does offer self-hosted streaming, but its docs say it needs an upfront commercial commitment and covers streaming, not every product.
• Language coverage. The top models cover 18 or 32 languages. If your users speak something else, you drop to Universal-2.
• Billing shape. Per-hour pricing plus add-ons can cost more than per-second billing for short, bursty clips.
• One-cloud policy. Some companies only approve vendors inside AWS, Google Cloud or Azure.
• You only need transcription. If you never touch the LLM features, a specialist or open-source model may be simpler.

The Best AssemblyAI Alternatives

Deepgram: the closest competitor for voice agents

Best for: real-time voice agents and apps with lots of short audio clips.

Deepgram's models overview lists Flux, a streaming model with turn detection built into the model, alongside Nova-3 for meetings, captions and noisy audio, and Nova-2 for languages Nova-3 doesn't cover yet. Turn detection is the piece voice agents struggle with most: knowing when someone has actually finished talking.

The Deepgram pricing page bills speech-to-text per second of audio, with no minimums. It also sells text-to-speech and a Voice Agent API. Self-hosted containers run in your VPC or on-prem on NVIDIA GPUs, on the Enterprise plan.

Where it's weaker than AssemblyAI: fewer built-in LLM features for summaries and analysis, and keyterm handling works differently, so re-test your vocabulary lists.

We compared Deepgram's own competitors in detail in our Deepgram alternatives guide, if you're weighing the two head to head.

Gladia: for audio that switches languages

Best for: products whose users mix languages in one conversation.

Gladia's models page lists Solaria-1 as the default: 100+ languages, async and live modes, and code switching. Solaria-3 is tuned for European business audio in English, French, German, Spanish and Italian, but it's pre-recorded only and doesn't code-switch. Both come with audio intelligence add-ons like diarization, translation, named entity recognition and PII redaction.

Where it's weaker than AssemblyAI: the most accurate model doesn't stream, so a live product sits on Solaria-1.

Speechmatics: when audio has to stay on your hardware

Best for: broadcasters, regulated industries and anyone with strict data residency rules.

Speechmatics' deployment docs cover a managed cloud plus on-prem CPU containers, GPU containers, Kubernetes and a virtual appliance. It offers realtime, batch and an Agent STT mode, with integrations for LiveKit, Pipecat, Vapi and Twilio.

This is the cleanest answer if self-hosting is why you're leaving. AssemblyAI's self-hosted offer covers streaming. Speechmatics treats on-prem as a standard deployment path.

Where it's weaker than AssemblyAI: on-prem means you run the GPUs, the upgrades and the monitoring.

ElevenLabs Scribe: for multilingual accuracy and speaker labels

Best for: multilingual recordings, and teams already using ElevenLabs voices.

The ElevenLabs speech-to-text docs recommend Scribe v3 for recorded audio and Scribe v3 Live for real time, across 90+ languages. Scribe v3 does speaker diarization for up to 32 speakers, keyterm prompting up to 1,000 terms, entity detection and mixed-language audio. ElevenLabs says it makes 27% fewer word errors than Scribe v2 on the FLEURS benchmark, which is the company's own number.

Where it's weaker than AssemblyAI: speech-to-text is one product inside a voice-generation company, and there's no self-hosting.

OpenAI: if you already pay for the OpenAI API

Best for: teams that want one vendor for language models and transcription.

OpenAI's speech-to-text guide now says to start with gpt-transcribe for recorded speech, and to use gpt-live-transcribe for live audio. It also says whisper-1, gpt-4o-transcribe, gpt-4o-mini-transcribe, gpt-4o-transcribe-diarize and the translations endpoint shut down on February 26, 2027. If an old tutorial points you at whisper-1, plan your migration now.

Where it's weaker than AssemblyAI: fewer speech-specific controls. There's no Medical Mode, and several of the guide's specialised examples still use the deprecated models.

Google Cloud Speech-to-Text: for Google Cloud teams

Best for: apps whose storage, IAM and billing already live in Google Cloud.

Chirp 3 is Google's latest multilingual speech model. Google says it improves on earlier Chirp models in accuracy and speed and adds diarization and automatic language detection. It runs only on the Speech-to-Text V2 API, through streaming, short sync requests and batch recognition.

Where it's weaker than AssemblyAI: more setup, and no equivalent of AssemblyAI's built-in LLM layer. You'd call Gemini separately.

Azure Speech: for Microsoft shops and edge devices

Best for: companies on Azure, and devices that need speech at the edge.

Microsoft's Azure Speech overview lists real-time transcription, fast transcription for files, and Azure LLM Speech, an LLM-powered model on the fast transcription endpoint. You can add custom vocabulary or train custom models. Microsoft also says you can run Azure Speech in the cloud or at the edge in containers.

Where it's weaker than AssemblyAI: lots of overlapping endpoints and model options. Expect to spend real time in the docs.

Rev AI: for English media and legal audio

Best for: media, legal and research teams who care most about English accuracy.

Rev AI's pricing page lists its Reverb model for English and foreign-language transcription, billed per hour of audio and rounded to the nearest second with a 15-second minimum. It also sells forced alignment, language ID, translation and human transcription through the same account. That last one is rare: you can send hard files to people.

Where it's weaker than AssemblyAI: fewer voice-agent features than AssemblyAI's streaming models, and no Medical Mode equivalent on its pricing page.

Whisper and faster-whisper: the open-source AssemblyAI alternative

Best for: offline transcription, sensitive audio and teams with spare GPUs.

OpenAI's Whisper repo is MIT-licensed and ships models from tiny to large, plus a turbo model that the README describes as an optimised large-v3 with minimal accuracy loss. The hosted whisper-1 API is being retired. The open-source weights are not.

faster-whisper reimplements Whisper on CTranslate2. Its README says it's up to 4 times faster than openai/whisper at the same accuracy, with less memory and optional 8-bit quantization.

Where it's weaker than AssemblyAI: everything around the model is on you. Streaming, diarization, PII redaction, summaries and scaling are all separate projects.

AssemblyAI vs Deepgram: The Head-to-Head

Most people searching for AssemblyAI competitors end up choosing between these two, so here's the short version.

Pick AssemblyAI if accuracy on recorded calls and meetings matters most, or you want transcription, redaction and LLM summaries from one vendor.

Pick Deepgram if you're building a voice agent where turn detection and per-second billing matter more than built-in analysis.

How to Choose an AssemblyAI Alternative

Before you sign anything, run the same test on every finalist:

1. Use your own worst audio. Thirty to sixty minutes of real recordings, including crosstalk, accents and product names. Benchmarks use someone else's audio.
2. Price the whole feature mix. Diarization, keyterms, redaction and medical vocabulary are add-ons at several vendors. Compare the total for your setup, not the headline rate.
3. Time it end to end. For live products, measure time to final transcript inside your own pipeline.
4. Check the deprecation calendar. OpenAI's February 2027 shutdown is a reminder that model names change. Pick a vendor whose migration notes you can live with.

If you'd rather buy a finished voice agent than wire one up from parts, our Vapi alternatives guide compares those platforms. And if what you actually want is a dictation app on your own Mac, not an API, see our Superwhisper alternatives guide.

Where Taku Fits

Taku isn't a speech-to-text API, and it doesn't replace AssemblyAI or anything on this list. It helps with a different problem: someone has already built a working transcription or voice tool on one of these APIs, and you'd rather use it than build your own.

That's where Taku comes in. Taku Apps and Sites, built by the best AI minds. Find one, run it, and keep it in your Mac Dock. Taku is in Beta, and the Mac app is available now. You can see what's there in the marketplace.

FAQ

Who are AssemblyAI's main competitors?

Deepgram is the closest, especially for voice agents. Gladia, Speechmatics, ElevenLabs Scribe and Rev AI are the other speech specialists. Google Cloud Speech-to-Text, Azure Speech and OpenAI compete as big platforms, and open-source Whisper competes on cost.

What is the best open source AssemblyAI alternative?

Whisper, run through faster-whisper for speed. Both are MIT-licensed and run offline. You'll need to add streaming, diarization and redaction yourself.

Is there a cheaper alternative to AssemblyAI?

It depends on your audio. Short, bursty clips often cost less with per-second billing like Deepgram's or Google's. Very high volume can be cheaper on self-hosted faster-whisper, once you count GPU and engineering costs. Always compare totals with your add-ons included.

Can I self-host AssemblyAI?

Partly. AssemblyAI's docs describe a self-hosted streaming stack that runs in your own infrastructure, sold with an upfront commercial commitment. For broader on-prem options, Speechmatics and Azure Speech containers are the usual picks.

AssemblyAI vs Deepgram: which is more accurate?

Neither wins on every kind of audio. AssemblyAI's Universal-3.5 Pro is built for accuracy on recorded speech with prompting. Deepgram's Flux is built for real-time conversations. Test both on your own recordings before you decide.