Amazon Polly vs Deepgram comparison

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Amazon Polly

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Executive SummaryUpdated on Apr 6, 2025

Amazon Polly and Deepgram are competitive products in the voice and speech recognition category. Amazon Polly appears to have the upper hand in pricing and support, while Deepgram excels in feature offerings and precision.

Features: Amazon Polly provides advanced text-to-speech capabilities, offering natural-sounding speech with a wide range of lifelike voices, supporting multiple languages and dialects. Deepgram is notable for high-accuracy speech recognition, customizable models, and seamless real-time processing, making it suitable for contexts where precision is key.

Room for Improvement: Amazon Polly could enhance its real-time processing capabilities and expand its customization options. Improved integration with non-AWS platforms would add value. Deepgram might benefit from more straightforward cost structures that cater to smaller businesses, broader language support, and simplified deployment processes for users less technically savvy.

Ease of Deployment and Customer Service: Amazon Polly offers easy deployment within the AWS ecosystem, backed by solid AWS support plans. Its integration into AWS services makes setup convenient for existing users. Deepgram provides a versatile deployment model, adaptable for cloud or on-premises use, requiring potentially more technical setup. Its customer service is known for its responsiveness and personalized approach.

Pricing and ROI: Amazon Polly's pricing is character-based, making it economical for budget-conscious businesses, ensuring good returns with low expenses. Deepgram charges based on processing hours, incurring higher costs justified by its accuracy and bespoke solutions. It offers significant value for businesses that prioritize precision and real-time processing, highlighting a trade-off between cost and advanced feature performance.

To learn more, read our detailed Amazon Polly vs. Deepgram Report (Updated: December 2025).

Amazon Polly vs. Deepgram

December 2025

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Amazon Polly

Ranking in Text-To-Speech Services

1st

Average Rating

7.4

Reviews Sentiment

7.6

Number of Reviews

Ranking in other categories

No ranking in other categories

Deepgram

Ranking in Text-To-Speech Services

4th

Average Rating

8.6

Reviews Sentiment

6.0

Number of Reviews

Ranking in other categories

Speech-To-Text Services (1st), AI Customer Support (5th), AI Sales & Marketing (7th), AI Scheduling & Coordination (2nd)

Mindshare comparison

As of January 2026, in the Text-To-Speech Services category, the mindshare of Amazon Polly is 21.7%, down from 33.1% compared to the previous year. The mindshare of Deepgram is 10.1%, up from 3.5% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Text-To-Speech Services Market Share Distribution
Product	Market Share (%)
Amazon Polly	21.7%
Deepgram	10.1%
Other	68.2%

Text-To-Speech Services

Featured Reviews

Anubhav Garg

Senior Software Developer at a tech vendor with 10,001+ employees

Text has been converted to speech across multiple languages with customizable voice settings

The most beneficial aspect of Amazon Polly is its ability to convert text to speech in multiple languages. It allows us to change the voice configurations for both male and female voices, and enables adjustments in pronunciation and delays. These features help us effectively target our users. Additionally, the integration capabilities with AWS services like Lambda aid us in storing Polly voice messages in DynamoDB and S3. It also offers configurations in multiple languages, enhancing our service reach.

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Arunkumar HG

Technology Architect & Hands-On Leader | Prototyping, Automation, AI/LLM Integration | 20+ Years in at Regalix

A Powerful, Adaptable, and Constantly Evolving STT Solution for Voice Automation

Honestly, Deepgram has been exceptionally proactive in addressing the primary area that needed improvement. My main challenge was with the real-time detection of when a user has finished speaking in a live conversation, which is critical for a responsive voice bot. They directly solved this by releasing their Flux model. Because Flux is a recent release, I haven't yet had enough time to thoroughly test it and identify new limitations. At this stage, any "improvement" would be more of a "nice-to-have" feature rather than a fix for an existing problem. The core service is already very robust and meets all of our current needs. What additional features should be included in the next release? ---------------------------------------------------------------- Looking toward the future, here are a few features that could add even more value to an already excellent platform: * Advanced Built-in Analytics: While I can get the raw transcript and build my own analytics pipeline, it would be powerful to have features like sentiment analysis, emotion detection, or automatic summarization offered directly through the API. This would save significant development time. * More Granular Speaker Diarization: For calls with multiple participants, enhancing the real-time speaker diarization (labeling who is speaking) to be even more precise would be a fantastic addition for creating detailed call analyses. * Tighter Integration with TTS: Since Deepgram is also expanding into Text-to-Speech (TTS), offering a more seamlessly integrated STT-to-TTS pipeline could simplify the development stack for creating voice agents from start to finish. * Specialized, Pre-Trained Industry Models: While the general models are highly accurate, offering even more specialized, pre-trained models for specific industries like finance, healthcare, or legal-which are heavy on specific jargon-could push the accuracy even higher for those niche use cases.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Amazon Polly offers significant features like the ability to select different voice categories and language options, such as Spanish, Portuguese, German, and French, which is particularly useful for maintaining worldwide contact centers and enhances customer experience by allowing us to give voice responses instead of text-based responses."

"Amazon Polly is useful because it's helpful to hear the words on top of it when I can't take in information in a general way. Sometimes, it's very taxing if I'm trying to read cases. They have the neural voices, and they're so realistic. You don't even know that a person is not reading to you, making things much better. I know that they do have the ability to provide you with your own lexicon that's personal to you. I like that you can adjust the pitch and the speed of the voice because some people talk way too fast. Or if you're reading, I read slowly, so that's always helpful. One of the functions that I find helpful is that when reading material on the web, it's like it has its own browser. You go to the URL, and you don't have to read the whole thing, and you can stick the cursor on the place where you want it to start. Then if you want it to skip over something, you put it somewhere else, and that's ideal for reading case law because you skip around a lot. You don't really read it from start to finish. It helps if someone's going to read all those citations because they definitely want to be able to skip that."

"We can use the SSML tags in Amazon Polly to modify text-to-speech by controlling speech patterns and behaviour."

"The sound generated by Amazon Polly is very natural, and I appreciate the options to select different voices, including an expensive or cheaper one, and the Structured Speech Markup Language (SSML) feature allows me to specify if I want a warmer or higher tune, which has helped make the meditations sound very natural."

"The most beneficial aspect of Amazon Polly is its ability to convert text to speech in multiple languages."

"The solution's Speech-to-Text conversion feature is really awesome."

"The speed of the solution for transcribing videos is good."

"The best thing with Deepgram is they are continually evolving and doing a lot of market research, and they take feedback seriously."

"The best features of Deepgram for me are the level of transcription accuracy it provides and the amount of time it saves."

"The most valuable capabilities of Deepgram that I've found so far include low latency, as it offers less than 200 milliseconds, which is not provided by any other text-to-speech models."

"Deepgram's transcription stands out compared to other solutions primarily due to its speed and accuracy; those are important points for me because not all providers or tools handled Spanish well, but Deepgram adjusted perfectly for that use case, and we also chose 11Labs voice, a South American voice, which worked very well with Deepgram."

"The recognition of industry-specific terminology phrases and abbreviations is really important for us. We were able to get a good level of industry specificity with Deepgram."

"Deepgram's low latency transcription has greatly impacted my ability to deliver reliable voice agents and provided very good transcription."

More Deepgram pros

Cons

"The price could be better. I wish it weren't so expensive to do because it's really cool. I would love to see them have lexicon packages of them like, this is for lawyers, this is for accountants, and it's going to have a lot of things in it. I also think they could do a better job at showing use cases other than telemarketing or contact center stuff like bots that are very commercial. I know that's where the money is, but it's such a huge hole that's missing for people with disabilities that are even worse than mine. Some people cannot see or hear at all, but they're not just cognitively impaired."

"When you put more tags inside Amazon Polly to define break time and instruct the speech to be conversational, sometimes it gives you an error."

"Amazon Polly's standard text-to-speech feature could be enhanced to deliver more natural and expressive human-like speech."

"The solution does not properly identify the number of speakers."

"Deepgram is currently restricted to only the English variants, but it should include other languages, such as German or French."

"Regarding improvements for Deepgram, I think the quality of the transcriptions could be enhanced, as the Spanish accent poses challenges, making it harder to transcribe some words, and considering additional accents from Chilean or Argentine speakers could improve the model's performance with local words."

"When I had an AI interview for coding, Deepgram didn't capture the names of programming languages or well-known LLMs accurately all the time."

"The traditional Speech-to-Text doesn't understand when the user is done speaking in bot conversations."

"Even though Deepgram has many customization options, I wish that Deepgram had voice cloning customization to a much larger extent."

"We haven't seen a return on investment with Deepgram so far; we have been building POCs for the last two years but recently switched to AWS in the last two months due to scalability issues with the pay-as-you-go model."

"The area of live transcription could be improved. Sometimes, Deepgram's WebSocket is disposed due to redundancy."

More Deepgram cons

Pricing and Cost Advice

"The solution has a pay-as-you-go pricing model, where you must pay according to your usage."

"The price could be better. Neural voices are so realistic, and I want to say that they have it so that you can try to tell where the voice is coming from or something like that. But if I have more than one, it's so expensive to have to listen to a bunch of cases on my phone and have the neural voice read to me. It really wouldn't be worth it. It'd be paying probably more than what I make in the case. Right now, I'm on the free tier, and I think the number of minutes that you get is reasonable as long as you're not doing this all the time and you're using it judiciously. I have some credits that I think I can use, but I don't know how fast they'll go through."

"Deepgram is a cheap solution."

"The pricing is moderate."

"When using Deepgram, one needs to pay for the hours or minutes for which the transcription is needed."

"The solution’s pricing is cheap."

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Top Industries

By visitors reading reviews

Educational Organization

Comms Service Provider

Computer Software Company

Financial Services Firm

10%

Comms Service Provider

University

Computer Software Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	8
Midsize Enterprise	1
Large Enterprise	1

Questions from the Community

What is your experience regarding pricing and costs for Amazon Polly?

Amazon Polly uses a pay-as-you-go pricing model. The standard voice type costs around $4 per one million characters, while the neural voice type costs approximately $10. It is free for the first tw...

What needs improvement with Amazon Polly?

Amazon Polly's standard text-to-speech feature could be enhanced to deliver more natural and expressive human-like speech. New speaking styles, emotions, more languages, and advanced features could...

What is your primary use case for Amazon Polly?

We are using Amazon Polly ( /products/amazon-polly-reviews ) to convert text into speech. It is being utilized to provide speech and voice messages to disabled users and also to deliver these speec...

What is your experience regarding pricing and costs for Deepgram?

My experience with pricing, setup cost, and licensing was good, as I found it to be cheaper without any problems.

What needs improvement with Deepgram?

Even though Deepgram has many customization options, I wish that Deepgram had voice cloning customization to a much larger extent. I also wish that the price were a bit lower if possible.

What is your primary use case for Deepgram?

My main purpose for Deepgram was to convert meeting voices to text very easily, and the other purpose was for content creation. I mostly use Deepgram for those two purposes.

Google Cloud Text-to-Speech vs Amazon Polly

Comparisons

Compared 49% of the time

Microsoft Azure Speech Service vs Amazon Polly

Compared 40% of the time

ElevenLabs vs Amazon Polly

Compared 6% of the time

IBM Watson Text To Speech vs Amazon Polly

Compared 3% of the time

More Amazon Polly Competitors

Gladia vs Deepgram

Compared 25% of the time

Microsoft Azure Speech Service vs Deepgram

Compared 22% of the time

Amazon Transcribe vs Deepgram

Compared 10% of the time

AssemblyAI vs Deepgram

Compared 10% of the time

More Deepgram Competitors

Product Reports

Download Amazon Polly product report

Amazon Polly

January 2026

Download Deepgram product report

January 2026

Overview

Amazon Polly is a service that turns text into lifelike speech, allowing you to create applications that talk, and build entirely new categories of speech-enabled products. Polly's Text-to-Speech (TTS) service uses advanced deep learning technologies to synthesize natural sounding human speech. With dozens of lifelike voices across a broad set of languages, you can build speech-enabled applications that work in many different countries.

In addition to Standard TTS voices, Amazon Polly offers Neural Text-to-Speech (NTTS) voices that deliver advanced improvements in speech quality through a new machine learning approach. Polly’s Neural TTS technology also supports two speaking styles that allow you to better match the delivery style of the speaker to the application: a Newscaster reading style that is tailored to news narration use cases, and a Conversational speaking style that is ideal for two-way communication like telephony applications.

Finally, Amazon Polly Brand Voice can create a custom voice for your organization. This is a custom engagement where you will work with the Amazon Polly team to build an NTTS voice for the exclusive use of your organization.

Amazon Web Services (AWS)

Deepgram stands out for its speed in transcribing videos and speech to text, leveraging cutting-edge models like Whisper and Nova for exceptional performance and accuracy. Its latency is remarkably low, enabling swift transcription that users find superior to alternatives.

Deepgram provides an efficient solution for transforming video and audio content into text, benefiting from its advanced ability to recognize industry-specific terminology. Users experience faster results compared to IBM Watson and OpenAI's Whisper model, with low latency contributing to its appeal. However, challenges in speaker recognition and language support remain areas for improvement. Additionally, stronger spelling and grammar accuracy could enhance its performance. Some seek expanded multi-language capabilities and improved manageability during testing phases, noting its slightly less accuracy compared to other tools.

What are Deepgram's most notable features?

Rapid Transcription: Utilizes cutting-edge models for quick speech-to-text conversion.
Industry Terminology Recognition: Excels in comprehending specific jargon and abbreviations.
Low Latency: Offers transcription with minimal delay, approximately 0.5 to 1 second.
Model Integration: Employs Whisper model combined with Nova for high accuracy.

What benefits should users look for when evaluating Deepgram?

High Speed: Significant improvement in processing time over competitors.
Performance Satisfaction: Users appreciate faster and more fluid transcription.
Textual Accuracy: Enhancements can lead to more reliable outputs in transcripts.
Streamlined Processes: Features like punctuation and Smart Format boost efficiency.

Deepgram is widely implemented across industries for transcribing speech to text, often used by organizations for generating machine transcripts of legal proceedings and other vital communications. Teams deploy it on local systems to convert videos and phone calls, integrating speech recognition seamlessly into applications.

Sample Customers

GoAnimate, Duolingo, Bandwidth

Information Not Available