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Meta: Muse Voice Transcribe 1.0

meta/muse-voice-transcribe-1.0
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Meta's speech-to-text model for streaming and file transcription, with speaker attribution and turn detection built into the model.
ModalitiesAudioText
In / out price— / — per 1M
Context—
Released—
ProvidersPricingPerformanceAvailabilityAppsActivityFAQExplore

Providers

Where this model runs, and what each route costs. Requests are sent to a healthy provider automatically; if one errors, the gateway retries against another serving the same model.

ProviderInput /MOutput /MCache read /MLatencyThroughput
Meta—————

Capabilities (8)

StreamingRealtimeDiarizationLanguage DetectionEndpointingVoice Activity DetectionCustom VocabularyZero Data Retention

Pricing

What this model costs to run, next to the rate it is posted at. Caching and discounts mean the price actually paid is often below the listed one.

Effective input price
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/M tokens
Effective output price
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/M tokens
RateListedChargedUnit
UTC
Price history starts building from the first daily snapshot — there is not enough of it yet to draw a trend.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better). Throughput and TTFT are measured on streaming requests, which are the only ones with a first-token moment to time.

Throughput
—tok/s
P50, streaming requests
Latency
—s
P50, end to end
UTC
No requests to this model in the selected window, so there is nothing to measure yet.

Availability

The share of requests to this model that completed successfully. When an upstream provider errors, the gateway retries against another provider serving the same model, so a single provider incident does not necessarily show up here.

Success rate (30d)
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over 0 requests
Days with traffic
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of the last 30
This model has not served any requests in the last 30 days, so there is no availability to report.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

No apps have identified themselves for this model yet. Clients can opt in by sending an X-Title header with their request.

Activity

Token volume and request traffic to this model over time. Daily totals, UTC.

No traffic in this window
Prompt0
Completion0

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length. Reasoning is not priced separately for this model, so it is not itemised here.

Frequently asked questions

What is Muse Voice Transcribe 1.0?
Meta's speech-to-text model for streaming and file transcription, with speaker attribution and turn detection built into the model.
How much does Muse Voice Transcribe 1.0 cost?
Pricing for Muse Voice Transcribe 1.0 is listed on this page under Pricing. You pay per request, with no subscription.
What is the context length of Muse Voice Transcribe 1.0?
The context window for Muse Voice Transcribe 1.0 is not published.
Does Muse Voice Transcribe 1.0 support tool calling and structured outputs?
Neither tool calling nor structured outputs are listed among this model's capabilities. Any unsupported parameter you send is ignored rather than rejected.
What inputs and outputs does Muse Voice Transcribe 1.0 support?
Muse Voice Transcribe 1.0 accepts audio as input and returns text.
What other models does Meta have?
Meta also offers Muse Glimmer, Muse Image 1.0, Muse Spark 1.1, Muse Spark 1.2 through Oxyy.
When was Muse Voice Transcribe 1.0 released?
No release date is published for Muse Voice Transcribe 1.0.

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