The best Gladia
alternative built
for full context.
Gladia turns audio into fast, accurate text through a developer API. Speak AI turns audio and video into full context, tone of voice, on-screen content, and a searchable system of record your team and your applications can both use.
Priya S.
Devin M.00:22 / 33:14
Why teams outgrow a transcription API alone
Gladia is a genuinely fast, accurate speech-to-text API built for developers. It was never built to be the product itself: there is no player, no team library, no video analysis, and no no-code path for a non-engineer. Here is the direct comparison.
| Feature | Speak AI | Gladia |
|---|---|---|
| Audio analysis (tone, emotion, energy) | Yes, on Scale plans | No. Gladia's audio intelligence covers sentiment and named entities in the text, not tone of voice |
| Video analysis (what's on screen) | Yes, on Scale plans | No video capture or analysis; audio only |
| Ready-to-use product (player, dashboard, library) | Yes, the full app is included | No. Gladia is API-only; you build the frontend |
| Embeddable recorder for non-developers | Yes | No, requires custom integration work |
| Shared, searchable archive across a team | Yes | No, teams build and host their own storage |
| Real-time streaming transcription | Yes | Yes, ultra-low-latency streaming is a real strength |
| Speaker diarization | Yes | Yes, well regarded diarization accuracy |
| Languages supported | 100+ | 100+, with native code-switching |
| NLP analytics across a whole library | Yes | No, sentiment and entities apply per request, not across recordings |
| MCP tools for Claude, ChatGPT, Cursor | 100+ tools across a full context engine | An official MCP server exists, scoped to calling the transcription API directly |
| No-code access for non-developers | Yes, no engineering required | No, a developer has to integrate the API first |
| AI voice agents | Yes | No |
| G2 rating | 4.9/5 | Limited G2 review volume as of August 2026 |
A transcript alone was never the whole conversation.
Gladia gives you fast, accurate text back from an API call. Speak AI reads the words, the voice, and the visuals together, ships as a finished product, and keeps all three searchable in one archive.
A team can use it the same day
Speak AI ships with the player, the shared library, the embeddable recorder, and the dashboard already built. Gladia is a strong API on its own; it still needs a team of engineers to become a usable product for anyone who isn't writing code.
Tone, emotion, and energy in the voice
Speak AI scores how a call actually sounded, beyond what was said. Frustration, hesitation, and confidence get flagged automatically, so coaching and QA go beyond a text transcript.
What's on screen, read and searched
When a screen is shared, Speak AI reads what was on it, slides, dashboards, a competitor's site, and ties it to the moment in the transcript. Gladia has no video capture or analysis at all.
Every source, one system
A meeting bot, an embeddable recorder, a mobile app, file uploads, and voice agents all land in the same searchable knowledge base, not five separate integrations you have to maintain.
Trends across the whole library
Keywords, sentiment, entities, and topics are extracted automatically and tracked over time, so patterns show up as a report instead of a one-off API response.
One system your other tools can query
Every transcript, audio signal, and screen read builds a context engine your team's applications draw on, through the API, webhooks, or the MCP server, no separate storage layer to build.
Gladia vs Speak AI: what each tool is actually built for
Gladia and Speak AI solve different problems for different buyers. Here is the honest breakdown, including where Gladia genuinely wins.
What Gladia does well
Gladia is a genuinely strong speech-to-text API. Its Solaria model line targets noisy, real-world business audio such as call centers and sales calls, and reports a 9.6% word error rate on real English audio with strong results across English, French, German, Spanish, and Italian (as of August 2026). Real-time streaming latency is fast, speaker diarization is well regarded, and 100+ languages with native code-switching mid-sentence is a real capability, not a marketing line. For a developer who needs raw, accurate transcription behind their own product, that is a legitimate reason to choose it.
Where an API stops being a product
Gladia returns text. It does not tell a coach that a prospect's voice tightened when price came up, or that they pulled up a competitor's pricing page mid-call, and it does not give a sales manager a shared library to search without engineering it first. Understanding the words, the voice, and the visuals together is the categorical difference between an API response and a context engine. Speak AI's audio analysis reads tone of voice, emotion in voice, and body language on screen, so a call scoring rubric or a coaching workflow has something real to grade, instead of a transcript and a sentiment score. This is multimodal analysis: the words, the tone of voice, and what's on screen together give a team the full context a raw transcription API cannot capture on its own.
Built for developers and no-code teams, not developers alone
Gladia's audience is developers: its docs, playground, and per-hour pricing all assume someone is going to write the integration. Speak AI is not the opposite of that. Speak AI ships a full API and an MCP server for custom applications, the same audience Gladia serves, plus the turnkey product on top: a recorder, a player, a shared archive, and a dashboard a research lead, a CS manager, or an agency owner can use without a developer in the loop. It is unified capture across a meeting bot, an embeddable recorder, a mobile app, file uploads, and voice agents, all landing in one searchable knowledge base your whole org can query.
Custom applications on top of the context
Because Speak AI keeps transcript, audio signal, and screen content together, teams build custom applications on top of it: dashboards, scoring rubrics, research coding, and AI voice agents, through the API or the MCP server. Gladia ships an official MCP server scoped to calling its transcription API; Speak AI's 100+ MCP tools work inside Claude, ChatGPT, and Cursor against a full system of record, transcript, audio signals, and screen reads included, which is what building better contextual knowledge on top of your conversations actually requires.
What a shared archive looks like in practice.
A national sports federation needed more than raw transcription output from its athlete and coach interviews.
"Speak AI helped us process hours of recorded athlete and coach interviews in multiple languages. We could finally identify themes and sentiment patterns across all our qualitative data in a fraction of the time."
The federation was running multilingual athlete and coach interviews and needed to transcribe field recordings, analyze sentiment across hundreds of sessions, and share findings organization-wide. A raw transcription API like Gladia could return the text, but the team would still have needed to build the storage, the search, and the analytics layer themselves. Speak AI handled all three out of the box: uploading recorded files, running NLP analytics across languages, and delivering a shared dashboard that saved the research team weeks of manual analysis.
Bring your context into Claude, ChatGPT, and Cursor.
Gladia ships an official MCP server, scoped to calling its transcription API: transcribe, translate, summarize. Speak AI's MCP server gives any assistant 100+ tools to search, analyze, and act on your full knowledge base, transcript, audio signals, and screen reads included, in about 60 seconds. No terminal, no npm, no config, backed by a full developer API.
Which one is right for you?
Both are good products. They are built for different jobs.
Choose Gladia if you…
- Are a developer who needs raw, accurate transcription behind your own product
- Need ultra-low-latency real-time streaming as the core building block
- Work with noisy, real-world business audio across many languages
- Want to pay per hour of audio and control every part of the stack yourself
- Don't need video analysis, a team library, or a no-code interface
Choose Speak AI if you…
- Need transcription, audio analysis, and video analysis, beyond text alone
- Want a finished product, recorder, player, library, on day one
- Need a shared archive the whole team can search, not a database you host
- Want NLP analytics and trends across hundreds of recordings
- Still want full API and MCP access for your own custom applications
- Need non-developers to use it without an engineering team
- Want white-label branding or AI voice agents included
Pricing comparison
Speak AI starts free to evaluate and scales by use. Gladia bills per hour of audio and assumes engineering time on top.
Speak AI
- Pay as you go: transcription and AI chat, credits-based
- Individual plan with transcription, storage, AI chat, and analysis included
- Team plan with shared libraries, collaboration, and priority support
- Enterprise: custom SSO, data controls, white-label, custom agents
- Free trial, more credits with a work email
Gladia
- Starter: async from $0.61/hour, real-time from $0.75/hour (as of August 2026)
- Growth: committed usage, rates as low as $0.20–$0.25/hour
- Enterprise: custom pricing, zero data retention, dedicated support
- Free evaluation credit for new accounts, no UI or team library included
Teams build on Speak AI.
Real feedback from teams using Speak AI for research, transcription, meetings, and client work.
Frequently asked questions
Common questions when comparing Speak AI and Gladia.
As of August 2026, Gladia's Starter tier bills per hour of audio: async transcription from $0.61/hour and real-time streaming from $0.75/hour, with a free evaluation credit for new accounts. Its Growth tier drops rates as low as $0.20–$0.25/hour for committed usage, and Enterprise pricing is custom. There is no built-in UI, player, or team library in any tier; that is a separate build.
It depends on what you're building. Gladia is a strong choice if you want a fast, accurate transcription API to embed in your own product, with real strengths in real-time latency, speaker diarization, and 100+ languages with code-switching. Speak AI is the better fit if you want transcription plus audio analysis, video analysis, a shared archive, and MCP access, without building the surrounding product yourself.
Gladia offers a free evaluation credit for new self-serve accounts, enough to test its transcription API before committing to paid usage. Speak AI offers a trial with credits that cover transcription, AI chat, and analysis, plus more credits with a verified work email, so you can evaluate the finished product, beyond the raw API.
For a developer building a custom voice product, Gladia's API is a legitimate, well-regarded choice. For a team that wants transcription, audio and video analysis, a shared searchable archive, and AI chat across every recording, without hiring engineers to build a frontend, Speak AI is the stronger fit.
Yes, especially once you need more than raw text back from an API. Speak AI adds a full product on top of transcription: audio analysis, video analysis, an embeddable recorder, a shared library, NLP analytics, multi-model AI chat, and 100+ languages. If you're a developer who only needs the transcription engine, Gladia is a strong, focused choice. If you need the whole system, Speak AI is the stronger fit.
No. Gladia's audio intelligence layer covers sentiment analysis and named entity recognition on the transcribed text, but it does not score tone of voice, emotion, or energy in the audio itself, and it has no video capture or analysis, so it cannot read what was on a shared screen. Speak AI analyzes all three and keeps them tied to the transcript.
Not really. Gladia is built for developers: its docs, playground, and pricing all assume someone is integrating the API into a product. There is no embeddable recorder, player, or dashboard for a non-technical user to pick up directly. Speak AI is usable by a research lead, a CS manager, or an agency owner with no engineering required, while still offering a full API and MCP server for teams that want to build on top.
Yes, Gladia ships an official MCP server, and it's scoped to calling its transcription API: transcribe, translate, and summarize audio through natural language. Speak AI's MCP server goes further, giving Claude, ChatGPT, and Cursor 100+ tools across a full context engine, transcript, audio signals, and screen reads included, not a thin wrapper around one API call.
Gladia charges per hour of audio processed, from $0.61–$0.75/hour on its Starter tier down to $0.20–$0.25/hour on committed Growth plans (as of August 2026), plus the engineering time to build a product around it. Speak AI offers a pay-as-you-go plan, an Individual plan, a Team plan, and a trial, with the player, library, and analysis already built in.
Start with Speak AI.
Transcription, audio analysis, video analysis, file uploads, NLP analytics, multi-model AI chat, and 100+ languages, in one shared archive with a full API and MCP server underneath. Book a free consult and see it on your own recording.
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