AssemblyAI vs Deepgram: Is Deepgram the Right Alternative?

Is Deepgram the right AssemblyAI alternative for your speech-to-text or voice AI stack? The useful answer depends on your audio, latency goals, deployment requirements, compliance review, and the wider product experience you want to build.

Quick answer: Choose Deepgram if you want batch and real-time speech-to-text, hosted or self-hosted deployment, and a unified Voice Agent API on one platform. AssemblyAI remains a candidate if your team already uses its APIs or depends on features it documents. Both vendors document self-hosting and a BAA pathway, so the deciding factor is a like-for-like test on your own audio.

This guide compares capabilities documented by AssemblyAI (Source A1) and Deepgram. Product plans and model availability change, so use the first-party sources at the end of this guide as a starting point and validate the final decision with your own audio and production requirements.

AssemblyAI (Source A1) and Deepgram both document APIs for converting pre-recorded and live audio into text. Their current product lines also extend into voice-agent workflows, language and domain features, and enterprise deployment options. The practical differences are model- and plan-specific.

Treat this table as a shortlist, not a benchmark result. Verify current entitlements and limits with each provider before choosing a plan.

Accuracy and speed are properties of a complete workload, not just a vendor name. Audio quality, speakers, accents, vocabulary, background noise, encoding, endpointing, and whether audio is live or pre-recorded can all change the result.

Start by defining the metrics that match your product. Word error rate (WER) is useful, but it should not be the only measure. A customer-support workflow may care about names, numbers, and speaker attribution. A voice agent may care more about time to first transcript, endpointing, interruptions, and tail latency.

Published test designs can help structure an evaluation, but they are not a substitute for a controlled test. Deepgram documents a reusable speech-to-text benchmark methodology. Run the same representative audio, normalization rules, and error analysis across the models you would actually deploy.

Both providers document model-specific language coverage. AssemblyAI's pricing and model table shows that language availability differs by model (Source A1). Deepgram's models and languages documentation likewise maps language and feature support to particular models.

Check the exact combination you need: language, locale, streaming or batch mode, diarization, formatting, vocabulary controls, and deployment type. For domain-heavy audio, build an evaluation set containing the terminology, names, abbreviations, and acoustic conditions your users produce.

For clinical audio, Deepgram offers Nova-3 Medical. Deepgram's March 3, 2025 announcement describes it as a speech-to-text model designed for clinical environments, built to capture medication names, diagnostic terms, and procedure details, with Keyterm Prompting for up to 100 custom terms. See Deepgram's medical transcription API for current capabilities. AssemblyAI documents a BAA request process (Source A5). For either vendor, test on permissioned medical audio that reflects your specialties, speaker roles, and documentation format.

Deployment requirements can narrow the shortlist before model testing begins. AssemblyAI documents self-hosted speech-to-text for selected products and environments (Source A3). Deepgram documents hosted and self-hosted options, including supported self-hosted environments.

Ask both providers which models and features are available in each deployment mode, how upgrades are delivered, what observability is included, and who operates capacity. If data location or infrastructure control is a requirement, include it in the proof of concept rather than treating it as a final procurement question. Deepgram's guide to on-premises speech-to-text deployment provides additional planning context.

Security claims should be evaluated against your organization's controls and contract requirements. AssemblyAI documents security controls and a sample BAA and request process (Sources A4–A5). Deepgram publishes privacy and compliance documentation, including its BAA pathway.

A vendor's certification or willingness to execute a BAA does not make your application compliant by itself. Review data retention, training use, subprocessors, access controls, audit evidence, incident terms, region support, and the products covered by the agreement.

Deepgram is worth evaluating when a team wants dated, published evidence for its shortlist and needs batch transcription, real-time streaming, enterprise deployment choices, or a unified voice-agent runtime. The following are Deepgram's own published results and capability statements, not independent validation and not claims about AssemblyAI.

In a publication dated February 12, 2025 and updated April 15, 2025, Deepgram reported a Nova-3 evaluation using 2,703 audio files across nine domains and 81.69 hours. Deepgram reported median WER of 6.84% for streaming audio and 5.26% for batch audio in that dataset. Review Deepgram's published Nova-3 evaluation for the methodology and domain list.

These are vendor-published results for a defined test set. Use them as a proof point for evaluation, then reproduce the test with your own audio and normalization rules.

In an article published November 27, 2025 and updated December 2, 2025, Deepgram stated that its systems deliver first-word latency near 150 milliseconds and described an end-to-end target below 300 milliseconds. Deepgram's streaming engineering article also recommends measuring p50, p95, and p99 latency.

Actual latency depends on network location, audio chunking, concurrency, configuration, and workload. Treat the published figure as Deepgram's system statement, not a guarantee for every deployment.

In an announcement published June 1, 2026 and updated June 4, 2026, Deepgram described its voice AI models as available through cloud APIs or self-hosted and on-premises APIs, and announced an on-premises confidential-computing solution with Fortanix and NVIDIA. See Deepgram's on-premises announcement.

Deepgram's current deployment documentation provides the plan and operational distinctions to confirm during procurement. Validate that the required model, infrastructure, updates, observability, and support terms are available in the selected deployment.

In its June 16, 2025 GA announcement, Deepgram documented a unified Voice Agent API combining speech-to-text, LLM orchestration, and text-to-speech. Deepgram also documented barge-in handling, turn-taking prediction, bring-your-own LLM or TTS options, and cloud, VPC, and on-premises deployment choices. See Deepgram's Voice Agent API GA announcement.

Teams should still evaluate the full interaction under realistic call patterns: endpointing, interruptions, model routing, tool calls, speech synthesis, monitoring, regional availability, and total operating cost.

Deepgram should be on the evaluation list for teams that:

• need both live and pre-recorded speech-to-text;
• want hosted and self-hosted deployment paths to evaluate;
• are building real-time conversational or voice-agent experiences;
• need to test vocabulary, language, diarization, and formatting behavior on domain audio; or
• prefer to evaluate speech recognition, speech synthesis, and voice-agent capabilities within one platform.

These are shortlist criteria, not a promise that one model will win every dataset. Validate them against current Deepgram documentation, your contract, and a representative proof of concept.

AssemblyAI may remain a strong evaluation candidate for teams already using its APIs or teams whose requirements align with its documented pre-recorded and speech-understanding products, streaming product, and self-hosted deployment options (Sources A1–A3).

If you are considering a migration, compare the capabilities you actually use rather than assuming parity from feature names. Test payloads, timestamps, speaker labels, formatting, retries, SDK behavior, and downstream data contracts.

Use a repeatable evaluation plan:

1. Define the job: batch transcription, captions, analytics, medical documentation, contact-center processing, or a real-time voice agent.
2. Select representative, permissioned audio across languages, devices, speakers, noise conditions, and edge cases.
3. Freeze the model versions and settings you are comparing.
4. Measure transcript quality with WER plus task-specific errors such as names, numbers, entities, speaker attribution, and formatting.
5. For streaming, measure partial and final transcript timing, endpointing, interruptions, and p50, p95, and p99 latency under expected concurrency.
6. Validate failure handling, observability, data retention, region, and deployment requirements.
7. Calculate cost using current Deepgram pricing and AssemblyAI's current pricing page (Source A1), then confirm discounts and commitments directly with each provider.
8. Run a limited production proof of concept before migrating traffic.

AssemblyAI (Sources A1–A3) and Deepgram both document current speech-to-text and voice AI products. The right choice depends on the models, features, deployment mode, compliance terms, operational behavior, and economics that fit your workload.

Deepgram is a compelling AssemblyAI alternative to evaluate if you want batch and real-time speech-to-text, hosted and self-hosted options, and a unified route into voice-agent development. The most defensible decision is still a current, like-for-like test using your own audio.

Ready to run that evaluation? Review Deepgram pricing or try the Deepgram speech-to-text API.

Deepgram is a relevant AssemblyAI alternative for teams evaluating real-time and pre-recorded speech-to-text, enterprise deployment options, or a unified voice-agent API. Whether it is the better fit depends on your audio, required features, deployment constraints, and proof-of-concept results.

Compare the complete spoken interaction: transcription and endpointing, interruptions, model choice, tool calls, text-to-speech, observability, deployment, and cost at realistic call duration and concurrency. AssemblyAI documents its current voice-agent path on its pricing page (Source A1); Deepgram documents its Voice Agent API.

Yes, both vendors currently document self-hosted speech-to-text options. AssemblyAI lists selected products and environments (Source A3), while Deepgram lists its deployment options. Availability, features, infrastructure, and plan requirements differ, so confirm the exact configuration with each provider.

Evaluate both against permissioned, representative medical audio and your required terminology, formatting, speaker roles, retention, security, and contract terms. Deepgram's dedicated option is Nova-3 Medical, covered in the medical transcription section above. AssemblyAI documents a BAA request process (Source A5), and Deepgram documents BAA availability. A BAA is only one part of your organization's compliance assessment.

Use AssemblyAI's current pricing page (Source A1) and Deepgram pricing for the exact model and processing mode you plan to use. Then model real usage, including audio duration, concurrency, add-on features, infrastructure for self-hosting, support, commitments, and any contracted discount. Avoid applying one headline multiplier across unlike models or workloads.

Use the same representative audio, model settings, preprocessing, normalization rules, and measurement window for both providers. Measure WER and business-critical errors, then add streaming latency and endpointing metrics if the workload is real time. Document model versions and test dates so the result can be reproduced when products change.

AssemblyAI first-party sources:

• A1. AssemblyAI. “Pricing.” https://www.assemblyai.com/pricing. Publication or update date not stated. Accessed 2026-10-01.
• A2. AssemblyAI. “Streaming Speech-to-Text.” https://www.assemblyai.com/products/streaming-speech-to-text. Publication or update date not stated. Accessed 2026-10-01.
• A3. AssemblyAI. “Self-Hosted Deployment.” https://www.assemblyai.com/deployments/self-hosted. Publication or update date not stated. Accessed 2026-10-01.
• A4. AssemblyAI. “Security.” https://www.assemblyai.com/security. Publication or update date not stated. Accessed 2026-10-01.
• A5. AssemblyAI. “Business Associate Agreement.” https://www.assemblyai.com/legal/business-associate-agreement. Last modified 2026-04-23. Accessed 2026-10-01.
• A6. AssemblyAI. “How can I make certain words more likely to be transcribed?” https://www.assemblyai.com/docs/faq/how-can-i-make-certain-words-more-likely-to-be-transcribed. Publication or update date not stated. Accessed 2026-10-01.

Deepgram first-party sources:

• D1. Deepgram. “Speech-to-Text API.” https://deepgram.com/product/speech-to-text. Accessed 2026-10-01.
• D2. Deepgram. “Models and Languages Overview.” https://developers.deepgram.com/docs/models-languages-overview/. Accessed 2026-10-01.
• D3. Deepgram. “Deployment Options.” https://developers.deepgram.com/docs/deployment-options. Accessed 2026-10-01.
• D4. Deepgram. “Self-Hosted Deployment Environments.” https://developers.deepgram.com/docs/self-hosted-deployment-environments. Accessed 2026-10-01.
• D5. Deepgram. “Data Privacy and Compliance.” https://developers.deepgram.com/trust-security/data-privacy-compliance. Accessed 2026-10-01.
• D6. Deepgram. “Voice Agent API.” https://deepgram.com/product/voice-agent-api. Accessed 2026-10-01.
• D7. Deepgram. “Pricing.” https://deepgram.com/pricing. Accessed 2026-10-01.
• D8. Deepgram. “What Is Word Error Rate?” https://deepgram.com/learn/what-is-word-error-rate. Accessed 2026-10-01.
• D9. Deepgram. “Speech-to-Text API Benchmarks.” https://deepgram.com/learn/speech-to-text-benchmarks. Accessed 2026-10-01.
• D10. Deepgram. “Choosing the Best Speech-to-Text On Premise Solution.” https://deepgram.com/learn/speech-to-text-on-premise-production-deployment. Accessed 2026-10-01.
• D11. Deepgram. “Introducing Nova-3.” https://deepgram.com/learn/introducing-nova-3-speech-to-text-api. Published 2025-02-12; updated 2025-04-15. Accessed 2026-10-01.
• D12. Deepgram. “Real-Time Transcription with Streaming Speech Recognition.” https://deepgram.com/learn/streaming-speech-recognition-api. Published 2025-11-27; updated 2025-12-02. Accessed 2026-10-01.
• D13. Deepgram. “Deepgram Delivers Private Voice AI to Regulated Industries.” https://deepgram.com/learn/deepgram-fortanix-press-release. Published 2026-06-01; updated 2026-06-04. Accessed 2026-10-01.
• D14. Deepgram. “Deepgram Launches Voice Agent API.” https://deepgram.com/learn/deepgram-launches-voice-agent-api. Published 2025-06-16. Accessed 2026-10-01.
• D15. Deepgram. “Keyterm Prompting.” https://developers.deepgram.com/docs/keyterm. Accessed 2026-10-01.
• D16. Deepgram. “Introducing Nova-3 Medical: The Future of AI-Powered Medical Transcription.” https://deepgram.com/learn/introducing-nova-3-medical-speech-to-text-api. Published 2025-03-03. Accessed 2026-10-01.
• D17. Deepgram. “Medical Transcription API.” https://deepgram.com/solutions/medical-transcription. Accessed 2026-10-01.