Speech-To-Text
Choosing between Deepgram and Gladia for your speech-to-text and audio intelligence needs often comes down to these five critical questions: How fast do you need results? How many languages do you support? What audio intelligence features matter most? How do you prefer to pay? What compliance certifications do you require?
Speech-To-Text
Deepgram has positioned itself as a comprehensive voice AI platform, offering everything from speech-to-text and text-to-speech to conversational AI capabilities. With its end-to-end, broad learning architecture and developer-focused approach, it has become a popular choice for enterprises building voice-enabled applications at scale.
Speech-To-Text
Deepgram has established itself as a major player in the speech-to-text space, offering developers and enterprises a fast, accurate transcription platform built on end-to-end deep learning. Its combination of real-time streaming, batch processing, and audio intelligence features makes it a go-to choice for companies building voice-enabled applications.
If you've ever navigated Deepgram's credit-based pricing system, trying to figure out if the $200 free credit will be enough while calculating per-minute rates that vary between streaming and pre-recorded audio, and then discovering that speaker diarization and entity detection are billed as add-ons, you know that speech-to-text API pricing can quickly become more complex than expected.
Navigating Deepgram's credit-based pricing system means figuring out whether the $200 free credit will be enough, calculating per-minute rates that vary between streaming and pre-recorded audio, and then discovering that features like speaker diarization and entity detection are billed as add-ons. Speech-to-text API pricing can quickly become more complex than expected.
Deepgram has established itself as a significant player in the voice AI market, processing over one trillion words with its end-to-end learning models and sub-300 millisecond latency. The platform offers a comprehensive suite including Speech-to-Text, Text-to-Speech, Audio Intelligence, and Voice Agent APIs, positioning itself as a full-stack voice AI platform.
But as Deepgram has expanded its feature set beyond core transcription, its pricing structure has become increasingly layered with base rates, add-on features, and a Model Improvement Program that affects your quoted prices.
After analyzing Deepgram's pricing tiers, credit system, and add-on costs Deepgram is the ideal choice if:
However, Deepgram's pricing is not a good choice if:
Gladia makes a relevant comparison point here as a speech AI platform that takes a different approach: transparent per-hour pricing with features like speaker diarization included, support for over 100 languages with code-switching, and an ongoing 10 free hours per month. As a pure-play speech-to-text provider, Gladia focuses exclusively on transcription and audio intelligence rather than expanding into competing voice AI products. Gladia also delivers leading partial latency in real-time transcription of approximately 103ms, roughly 2x faster than Deepgram, which is particularly relevant for voice agent applications.
This article provides a detailed pricing comparison between Deepgram and Gladia to help teams evaluate the total cost of ownership for each platform. To skip directly to the Gladia pricing breakdown, use the link below.
Table of Contents
Before diving into the detailed breakdown, it's important to understand that both Deepgram and Gladia offer two distinct transcription modes with different pricing: real-time (streaming) for live audio and async (pre-recorded/batch) for uploaded files.
Because Gladia's pricing inherently includes 100+ languages and bundled audio intelligence features, the Deepgram rates shown below use the Nova-3 Multilingual model (the most comparable tier) and factor in common STT add-ons where applicable.
Note that Deepgram's Audio Intelligence features (Sentiment Analysis, Topic Detection, Summarization, Intent Recognition) are priced per token rather than per minute, making direct inclusion in per-minute rates impossible. These represent additional costs not reflected in the rates below.
Deepgram operates on a usage-based credit system where customers purchase credits upfront and these credits are deducted as they use the APIs.
The platform offers three main tiers: Pay-As-You-Go for flexibility, Growth for committed volume discounts, and Enterprise for custom needs. Billing is calculated per second of audio processed (not rounded up to the minute), with different rates for streaming (real-time) versus pre-recorded (async) audio. Understanding this distinction is important because streaming rates are generally higher than pre-recorded rates across all models.
The Pay-As-You-Go plan provides immediate access to all of Deepgram's public models and endpoints without any minimum commitment.
The $200 free credit allows extensive testing before committing funds, though promotional credits expire one year from signup. This tier targets developers and small teams who need flexibility without long-term contracts.
The Bottom Line 👉 Pay-As-You-Go suits developers testing Deepgram's capabilities, but teams with consistent volume should consider Growth for better rates.
The Growth plan rewards committed usage with up to 20% savings across services. Credits are pre-paid for the year and expire after 12 months unless the plan is renewed or upgraded.
This tier targets growing businesses with predictable transcription needs who can commit to the annual minimum.
The Bottom Line 👉 Growth delivers meaningful savings for teams processing consistent volume, but the annual commitment and expiring credits require careful planning.
Enterprise plans provide the highest discounts and most flexibility, including access to custom-trained speech-to-text models and self-hosted deployment options.
This tier targets organizations with large-scale needs or specialized use cases requiring custom model training.
The Bottom Line 👉 Enterprise suits organizations needing custom models or on-premises deployment, but most teams won't need this level of customization.
Beyond base transcription rates, several features incur additional charges:
Speech-to-Text Add-ons:
Audio Intelligence Features (Token-Based Pricing):
Deepgram's Audio Intelligence features, including Sentiment Analysis, Topic Detection, Summarization, and Intent Recognition, are priced per token ($0.0003/1k input tokens, $0.0006/1k output tokens on Pay-As-You-Go) rather than per minute. This billing model makes direct per-minute comparison with all-inclusive providers difficult. Translation is also not available as a Deepgram STT add-on.
Multichannel Audio: Each channel is billed separately. A stereo file costs twice the single-channel rate.
Model Improvement Program: Listed rates assume opt-in to Deepgram's Model Improvement Program. Customers can opt out using the mip\_opt\_out=true parameter, though this means forgoing the 50% discount reflected in standard pricing.
While Deepgram offers robust speech recognition with competitive latency and comprehensive API options, its pricing structure and strategic direction create challenges for certain use cases:
Complex Add-On Pricing Structure
Expanding Beyond Core STT
Deepgram has evolved from a speech-to-text provider into a full-stack voice AI platform, now offering Text-to-Speech (Aura), Voice Agent APIs, and LLM integrations.
Source: Deepgram
While this expansion provides value for teams wanting a unified platform, it creates a consideration for companies building voice agents or conversational AI products: your STT provider may now be offering products that compete with what you're building. This horizontal expansion could also have an impact on their STT quality, as companies that expand across multiple product areas may become less focused on delivering top accuracy on each individual building block of the workflow, such as STT or TTS.
Multilingual Code-Switching Limitations
One-Time Free Credit Model
Data Privacy Trade-offs
These limitations have led many teams to explore alternatives that offer more transparent, all-inclusive pricing.
Gladia simplifies speech-to-text pricing by including features like speaker diarization in base rates and offering transparent per-hour pricing.
For teams who find Deepgram's add-on pricing complex, language coverage limiting, or data privacy trade-offs concerning, Gladia offers an alternative. Built on their Solaria-1 model that has a 94% word accuracy rate with 270ms latency while reducing disturbances common in real-world, noisy audio, Gladia serves over 700 enterprise customers, including teams at VEED.IO, Attention, and Circleback.
What distinguishes Gladia strategically is its positioning as a pure-play speech AI provider.
While competitors expand into Text-to-Speech and Voice Agent products, Gladia stays focused on transcription and audio intelligence. For companies building voice agents or conversational AI, this means Gladia remains a partner rather than a potential competitor.
On data privacy, Gladia's approach treats your audio as non-negotiable: paid-tier customer audio is never used for model training. Only Free-plan data may be used for improvements. There's no opt-out pricing penalty or discount to forfeit.
Unlike Deepgram's add-on model, Gladia's Pro plan includes speaker diarization, sentiment analysis, and language detection in the base price.
The ongoing 10 free hours monthly means teams can maintain low-volume usage without payment.
The Bottom Line 👉 Pro delivers predictable costs with audio intelligence features included, suited for teams wanting to avoid add-on calculations.
The Scaling plan provides volume discounts while maintaining all-inclusive pricing. The automatic model training opt-out is included without affecting price.
This makes it attractive for organizations handling sensitive audio who don't want data privacy to be a cost trade-off.
The Bottom Line 👉 Scaling model suits growing teams needing better rates and data privacy guarantees without Enterprise complexity.
Enterprise plans provide unlimited concurrency and enhanced data retention options for organizations with strict compliance requirements. Gladia offers dedicated infrastructure in both US and Europe, ensuring data residency flexibility for global operations.
Deepgram's Approach: Deepgram uses per-minute pricing with separate add-ons for features like speaker diarization, redaction, and keyterm prompting. Audio Intelligence features (Sentiment Analysis, Topic Detection, Summarization) are billed per token rather than per minute, adding another layer of cost calculation. Multichannel audio multiplies the cost. The Model Improvement Program opt-out doubles rates.
Gladia's Approach: Gladia uses per-hour pricing with audio intelligence features included in the base rate. Speaker diarization, language detection, sentiment analysis, and code-switching don't incur additional charges. The pricing page explicitly states "no setup fees or hidden costs."
🪙 Value Verdict: Gladia is better for teams wanting predictable costs without add-on calculations, while Deepgram offers granular control for teams who only need basic transcription without additional features.
Deepgram's Approach: Deepgram's Nova-3 Multilingual model supports code-switching across 10 languages: English, Spanish, French, German, Hindi, Russian, Portuguese, Japanese, Italian, and Dutch. Nova-3 continues to expand with additional language support.
Gladia's Approach: As a European-founded company, Gladia was built with multilingual support as a foundation rather than an afterthought. The platform supports over 100 languages with automatic language detection and code-switching, including 42 languages underserved by other providers.
Source: Gladia
The Solaria model was benchmarked on datasets like Mozilla Common Voice and Google FLEURS, which are designed to test performance across diverse accents and dialects.
🪙 Value Verdict: Gladia is better for global teams with multilingual conversations, regional language requirements, or audiences speaking underserved languages. Deepgram's code-switching covers the most common language pairs but with a narrower scope.
Deepgram's Approach: Deepgram has established a reputation for competitive latency, with Nova-3 delivering sub-300ms performance. The platform was designed for real-time applications, including voice agents and live captioning.
Gladia's Approach: Gladia positions itself as "real-time first, async-ready". The platform was designed from the ground up for real-time conversational use cases. Solaria delivers approximately 103ms partial latency (time to first transcript), which is roughly 2x faster than Deepgram's partial latency, and approximately 700ms final latency, benchmarked for voice agent and contact center environments.
🪙 Value Verdict: Gladia delivers faster partial latency, which is particularly relevant for voice agents where natural conversational flow depends on minimizing response delays. Both platforms deliver strong real-time performance suitable for conversational AI.
Deepgram's Approach: Deepgram offers Keyterm Prompting to improve recognition of brand names and domain-specific vocabulary. Entity detection is available as an Audio Intelligence feature with separate token-based pricing.
Gladia's Approach: Gladia bundles custom vocabulary and named entity recognition into base pricing. These features allow teams to prompt the model with specific terminology useful for accurately transcribing email addresses, names, numbers, and industry jargon in domains like medical, financial, and legal transcription.
Source: Gladia
🪙 Value Verdict: Both platforms offer precision features. Gladia includes them in base pricing; Deepgram charges separately. For teams processing specialized terminology, Gladia's bundled approach may provide better value.
Deepgram's Approach: Deepgram provides a generous $200 one-time credit, though promotional credits expire one year from signup. Purchased credits never expire. However, once credits are exhausted, there's no free tier for ongoing low-volume use.
Gladia's Approach: Gladia offers 10 free hours of transcription every month as part of their free plan. This ongoing refresh allows sustained low-volume usage. Additionally, custom discount offers are available to startups under the Scaling plan.
🪙 Value Verdict: Deepgram is better for extensive initial testing ($200 worth), while Gladia is better for ongoing low-volume needs with its monthly refresh.
Deepgram's Approach: Standard pricing assumes participation in Deepgram's Model Improvement Program. Customers can opt out using the mip\_opt\_out=true parameter, but this means forgoing the 50% discount reflected in standard rates.
Gladia's Approach: Gladia automatically opts out paid-tier customers from model training. Only Free-plan audio may be used for model improvements. This approach reflects the position that customer data shouldn't be a bargaining chip.
🪙 Value Verdict: Gladia provides simpler privacy controls for paid customers with automatic opt-out and no cost trade-off. Deepgram requires explicit opt-out at higher cost.
Deepgram's Approach: Deepgram has expanded from speech-to-text into a full voice AI platform, offering Text-to-Speech (Aura), Voice Agent APIs, and LLM integrations. This provides a unified stack for teams wanting everything from one provider.
Gladia's Approach: Gladia remains a speech AI provider focused exclusively on transcription and audio intelligence. Gladia deliberately doesn't offer TTS or complete voice agent solutions, staying vertical in the speech recognition space rather than expanding horizontally. This focus allows Gladia to provide top-tier quality and performance on its core offering.
Source: Gladia
🪙 Value Verdict: Teams wanting a complete voice AI stack may prefer Deepgram's breadth. Teams building their own voice agents or conversational AI products may prefer Gladia's focused approach, ensuring their STT provider remains a partner rather than a potential competitor.
Deepgram provides $200 in free credit upon signup, with no credit card required. This credit provides access to all public models and endpoints. However, promotional credits expire one year from signup, and once the credit is exhausted, payment must be added to continue. There's no ongoing free tier with monthly refresh.
The Pay-As-You-Go plan has no minimum purchase beyond using your free credit. The Growth plan requires a $4,000+ annual commitment for the discounted rates. Enterprise pricing is custom.
Purchased Pay-As-You-Go credits never expire. However, the initial $200 promotional credit expires one year from signup. Growth plan credits expire after one year unless the plan is renewed or upgraded. Refunds for unused Pay-As-You-Go credits are available if requested within 30 days of purchase.
Speaker diarization is included for pre-recorded transcription but is billed as a streaming add-on at $0.0020/min (Pay-As-You-Go) on top of base transcription costs. This contrasts with Gladia, where speaker diarization is included in the base price at no additional charge across both real-time and async modes.
Gladia supports over 100 languages with code-switching capability, including 42 underserved languages not covered by other providers. Deepgram's Nova-3 Multilingual supports code-switching across 10 languages (English, Spanish, French, German, Hindi, Russian, Portuguese, Japanese, Italian, and Dutch).
For teams with speakers who switch between languages beyond this set, or who need broader language coverage, Gladia offers stronger capabilities.
No, Gladia focuses on speech-to-text and audio intelligence. Deepgram offers Text-to-Speech (Aura) and Voice Agent APIs that Gladia doesn't provide. Teams needing TTS capabilities should consider Deepgram or pair Gladia with a separate TTS service. This reflects Gladia's strategic choice to remain a speech AI provider rather than expanding into competing product areas.
Deepgram's standard pricing assumes customers opt into their Model Improvement Program. Opting out via the mip\_opt\_out=true parameter means forgoing the 50% discount. Gladia takes a different approach: paid-tier customers are automatically opted out of model training with no pricing impact. Only Free-plan data may be used for improvements.
The choice between Deepgram and Gladia depends on your specific needs, technical requirements, and strategic considerations:
👍 Deepgram is a comprehensive voice AI platform for teams wanting more than transcription from a single provider. With usage-based pricing starting from $0.0052/min for pre-recorded audio (Nova-3 Multilingual), a $200 free credit, and an expanding product suite including Text-to-Speech and Voice Agent APIs, it enables developers to build complete voice applications from one vendor.
This approach works best for teams building voice agents who want a unified API stack, organizations requiring Text-to-Speech alongside transcription, enterprises needing self-hosted or on-premises deployment, and developers who can leverage the large initial free credit for extensive testing.
Get started with Deepgram here.
👉 Gladia is a speech AI platform built on transparent, all-inclusive pricing and a focused product strategy. By offering 10 free hours monthly with speaker diarization included, support for 100+ languages with code-switching, and automatic data privacy opt-out on paid plans with no pricing penalty, it provides predictable costs without add-on calculations.
As a speech-to-text provider, Gladia commits to staying focused on transcription and audio intelligence rather than expanding into competing voice AI products. This makes it well-suited for teams building voice agents who want an STT partner that won't compete with them, global teams with multilingual transcription needs across diverse language combinations, organizations handling sensitive audio who want privacy without cost trade-offs, and teams wanting ongoing free usage rather than one-time credit.
The distinction isn't just about pricing structure, it's about strategic alignment. Deepgram is building toward a complete voice AI platform; Gladia is committed to being the best speech-to-text infrastructure layer. For teams building their own voice products, that difference in trajectory may matter as much as today's feature comparison.
