MAI-Transcribe 2 Reaches 8.22 Million Weekly Requests on OpenRouter as Adoption Grows

MAI-Transcribe 2 handled 8.22 million transcription requests in OpenRouter's latest complete week of ranking data, up 18% from the previous week. The model's sustained usage makes it the third-most-used transcription model on the platform, behind Whisper variants, and points to broad demand for speech-to-text services that can be accessed through a common model gateway.

The scale matters because transcription is becoming a practical building block rather than a specialist media task. Teams can turn calls, interviews, voice notes, support recordings, and video into searchable text, then use that text in documentation, captioning, or follow-up workflows. OpenRouter's official transcription rankings show that MAI-Transcribe 2's growth is continuing across multiple weeks, rather than being limited to an initial launch spike.

What the OpenRouter data shows

OpenRouter's English rankings place MAI-Transcribe 2 at 8.22 million requests for the most recent complete week in early November 2026. The ranking reports a 18% week-over-week increase. A mirrored Chinese-language view showed a similar recent range of roughly 8.5 million to 8.6 million requests, while the platform's data has consistently placed recent weekly volumes in the multi-million range.

The reported trajectory is also consistent with the claim that requests have risen about 12 times since launch. MAI-Transcribe 2 launched in September 2026, and the early volume cited was 0.7 million requests in its first week. The latest figure should be read as request volume on OpenRouter, not as a count of customers, audio hours, or distinct recordings.

Usage rankings do not explain precisely why every developer or business selected a model. However, reporting from VentureBeat positioned MAI-Transcribe 2 around a launch price of $0.10 per hour and highlighted speed, price, and speaker diarization as competitive characteristics. Speaker diarization is the process of identifying or separating speakers in an audio recording. That capability can be particularly useful where a transcript needs to distinguish participants in a meeting, interview, or customer call.

Why the surge matters for business workflows

A low per-hour transcription price can change the economics of working with audio. Instead of reserving transcription for exceptional recordings, a team can consider making routine spoken material available as text. The value is not simply in producing a transcript. It is in making audio easier to search, review, reuse, and pass into the systems people already use.

Potential uses include:

• Creating a text record from internal meetings before preparing notes or action items.
• Producing transcripts that can support video captions and content repurposing.
• Converting interviews and research calls into material that is easier to review.
• Making voice notes and recorded customer conversations more searchable.

The model's position on OpenRouter is also relevant to developers and teams building workflows around multiple AI providers. OpenRouter's rankings indicate that MAI-Transcribe 2 is available through its transcription offering, giving users a route to evaluate it alongside other models accessed through the platform. Its ranking behind Whisper variants shows that the market remains competitive, rather than indicating that one transcription option has displaced all others.

For practical adoption, request counts are only one signal. Businesses still need to test transcript quality against their own audio conditions, including accents, terminology, multiple speakers, recording quality, and the languages they use. A model that performs well on clean audio may require different handling for a noisy call or a discussion involving specialized vocabulary. Teams should also decide what happens after transcription, such as where text is stored, who reviews it, and whether a separate tool generates summaries or follow-up tasks.

As transcription volumes rise, the larger opportunity is connecting speech-to-text to repeatable processes rather than treating each recording as a one-off file. Scalevise helps businesses design AI workflow automation for transcription and follow-up processes, connecting audio intake, transcription, review, summaries, and downstream actions while keeping human checks where they matter. If your team spends time replaying calls or manually moving notes between tools, discuss an AI automation project with Scalevise.

Frequently Asked Questions

What is MAI-Transcribe 2?

MAI-Transcribe 2 is a transcription model available in OpenRouter's transcription rankings. It converts audio into text and is listed as the platform's third-most-used transcription model in the latest complete week cited.

How many requests did MAI-Transcribe 2 receive on OpenRouter?

OpenRouter's English transcription ranking reported 8.22 million MAI-Transcribe 2 requests in the latest complete week of data in early November 2026. That was 18% higher than the previous week.

What is the reported price of MAI-Transcribe 2?

VentureBeat reported a launch price of around $0.10 per hour. Businesses should check the current OpenRouter listing before budgeting or deploying a workflow, because pricing can change.

Can MAI-Transcribe 2 be used for meeting notes or captions?

It can provide the transcription step for workflows involving meeting records, captions, interviews, and other audio. Notes, summaries, captions, and task creation may require additional tools or review steps beyond the transcript itself.

Conclusion

MAI-Transcribe 2's 8.22 million weekly requests on OpenRouter show that its adoption is continuing well beyond launch. Its reported price point and diarization capability help explain why transcription is increasingly viable for routine business audio, but the most useful implementation will depend on transcript quality, workflow design, and appropriate human review.