Deepgram vs Whisper: Nova-3 and Whisper API Compared

November 7, 2026

Deepgram Nova-3 is a proprietary speech-to-text model that Deepgram runs as a hosted API, with both file transcription and live streaming. Whisper is an open-weight model from OpenAI: you can run it yourself, call OpenAI’s hosted whisper-1, or use another host such as Groq or Cloudflare. Through Speechall, the Whisper models are file-only, while Nova-3 also streams.

That difference, a single vendor’s hosted model versus an open model offered by several hosts, shapes most of the practical choice. It affects which features you get, what you pay per audio hour, and whether you can process live audio. Accuracy is a separate question, and the answer depends on your recordings. This guide compares the published facts and shows how to test both on the same file.

Rates and capabilities below come from the Speechall model catalog as of November 2026. They are Speechall credit usage, not provider list prices, and they can change. Check each model page before you estimate costs.

Deepgram Nova-3 vs Whisper at a glance

A few things stand out:

• Live audio: Nova-3 is the only model in this group that Speechall can stream over its WebSocket endpoint. If you need live captions or a voice interface, the Whisper hosts in this table do not cover it.
• Speakers: Nova-3 has speaker diarization, which separates who spoke when. None of the Whisper entries do.
• Cost: hosted Whisper ranges from $0.0306 to $0.36 per audio hour depending on the host. Nova-3 sits in the middle at $0.312 for files.
• Languages: the Whisper entries list 57 languages in the catalog and Nova-3 lists 15. Coverage is not the same as quality in a given language, so test the languages you need.
• Subtitles: if you want SRT or VTT files straight from the API, check the subtitle row. Support differs even between hosts of the same Whisper model.

What “Whisper” means depends on the host

Whisper’s code and model weights are published under the MIT license in OpenAI’s whisper repository. That is why several companies offer it. The model is the same family, but each host sets its own price, limits and output options.

• OpenAI whisper-1 is OpenAI’s hosted version. OpenAI’s speech-to-text guide limits uploads to 25 MB and suggests compressing or splitting longer recordings.
• Groq serves Whisper Large v3 and the faster Large v3 Turbo variant at lower per-hour rates on Speechall.
• Cloudflare Workers AI serves Whisper Large v3 Turbo at the lowest rate in this table, with a smaller 10 MB file limit.
• Self-hosting is also possible. You avoid per-minute API charges but take on GPUs, scaling, queueing and model updates.

Deepgram Nova-3 is not open-weight: you use it through Deepgram, directly or through a gateway such as Speechall. For Deepgram’s own rates, plans and deployment options, see Deepgram’s pricing page.

When to choose Deepgram Nova-3

• You need live transcription, such as captions, call transcription or a voice agent.
• You need speaker diarization for meetings, interviews or support calls.
• Your files are larger than 25 MB and you would rather not split them. The catalog does not list a file-size limit for Nova-3, so confirm the limit for your workload before you rely on it.
• Nova-3 covers your languages. Check the model page for the list.

When to choose Whisper

• You transcribe recorded files and do not need speaker separation.
• Cost per hour matters most. The Groq and Cloudflare hosts are the lowest rates in this comparison.
• You need broad language coverage, or you want the option to self-host the same model later.
• You want SRT subtitles directly from the API. OpenAI’s whisper-1 lists both SRT and VTT.

Test both on your own audio

Published benchmarks rarely match your microphones, accents, background noise or vocabulary. The most reliable comparison is to send the same recordings to both models and score the results.

With Speechall, the two requests differ only in the model query parameter. Replace the file path and YOUR_API_KEY, then run:

# Deepgram Nova-3
time curl -X POST "https://api.speechall.com/v1/transcribe?model=deepgram.nova-3&language=en&output_format=text" 
     -H "Authorization: Bearer YOUR_API_KEY" 
     -H "Content-Type: audio/wav" 
     --data-binary @meeting.wav > nova-3.txt

# OpenAI Whisper (swap in groq.whisper-large-v3-turbo to test another host)
time curl -X POST "https://api.speechall.com/v1/transcribe?model=openai.whisper-1&language=en&output_format=text" 
     -H "Authorization: Bearer YOUR_API_KEY" 
     -H "Content-Type: audio/wav" 
     --data-binary @meeting.wav > whisper-1.txt

To make the test useful:

1. Use 10 to 20 representative files, not one clean sample. Include your hardest audio: crosstalk, phone quality and domain terms.
2. Write reference transcripts for a subset and compute word error rate (WER) for each model. Normalize punctuation and casing the same way for both.
3. Record processing time from the time output if turnaround matters for your product.
4. Multiply audio hours by each rate to compare cost for your monthly volume. The cost guide covers retries, review time and credit fees.
5. Check the features you depend on, such as timestamps, speaker labels or subtitle files, using the output_format options in the getting started guide.

Because the request shape stays the same, you can add more candidates to the same script, for example the other models in the catalog.

When to integrate directly instead of through Speechall

A gateway is not always the better route. Integrate with Deepgram or OpenAI directly when:

• You depend on a provider-specific feature that Speechall does not expose for that model.
• You have negotiated pricing, committed-use terms or a data-processing agreement with one provider.
• You have settled on a single model and do not expect to compare or switch.
• You plan to self-host Whisper for cost or data-residency reasons.

Speechall is most useful when you want to compare models on your own audio, expect to switch later, or want several providers behind one API key and one bill. The gateway vs direct integration guide walks through the trade-offs in more detail.

Summary

Deepgram Nova-3 and Whisper solve overlapping problems in different ways. Nova-3 is a single-vendor hosted model with streaming and speaker diarization. Whisper is an open model whose price, limits and outputs depend on who hosts it. Use the table above to narrow the choice by required features, then let a word-error-rate test on your own recordings decide.