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Model infoModelsSnapshot: 15 Oct 2026

Microsoft AI / NaturalSpeech 3

NaturalSpeech 3 (1B)

Factorized diffusion speech research system that separates content, prosody, timbre and acoustic detail. The scaled experiment uses one billion diffusion-model parameters and 200,000 hours of internal data.

restrictedClosed weightsText-to-speech
Official documentation (opens in a new tab)Reviewed 14 Oct 2026
12 of 25 specification fields collected
Audio sample rates16 kHz speech in the reported systemSee specification notes below
LanguagesNot collectedAwaiting source review
Input billingNot collectedMicrosoft Research (prerecorded samples)
Output billingNot collectedNo inferred price

Specifications

Provider-documented facts. “Not collected” means we have not verified that field yet, not that the feature is unsupported.

Context / input limit
Not collected

No public service contract or verified value for this original research checkpoint.

Maximum input tokens
Not collected

No public service contract or verified value for this original research checkpoint.

Maximum output
Not collected

No public service contract or verified value for this original research checkpoint.

Parameters
1B factorized diffusion modelSource for Parameters (opens in a new tab)

Section 4.4 model-scale label; not a verified total including every codec and auxiliary component.

Reasoning
Not collected

No public service contract or verified value for this original research checkpoint.

Tool calling
Not collected

No public service contract or verified value for this original research checkpoint.

Structured output
Not collected

No public service contract or verified value for this original research checkpoint.

Streaming
Not collected

No public service contract or verified value for this original research checkpoint.

Batch processing
Not collected

No public service contract or verified value for this original research checkpoint.

Fine-tuning
Not collected

No public service contract or verified value for this original research checkpoint.

Context caching
Not collected

No public service contract or verified value for this original research checkpoint.

Knowledge cutoff
Not collected

No public service contract or verified value for this original research checkpoint.

Release date
Not collected

No public service contract or verified value for this original research checkpoint.

Languages
Not collected

The 200K-hour internal training corpus does not provide a complete supported-language list. English evaluation does not establish an exhaustive inventory.

Research publication
2024-03-05Source for Research publication (opens in a new tab)

First research-family disclosure on arXiv; reviewed specifications may reflect a later paper revision. Not a commercial or separate variant release date.

Endpoint availability
Research paper and prerecorded samples. No public full-model download or interactive inference service found in reviewed original materials.Source for Endpoint availability (opens in a new tab)
Voice cloning
SupportedSource for Voice cloning (opens in a new tab)

Zero-shot research use of a reference voice, not an available commercial API.

Reference audio
Reference speech conditions the individual speech attributes; three-second prompts used in the LibriSpeech evaluation.Source for Reference audio (opens in a new tab)

An evaluation setting, not an advertised maximum reference duration.

Architecture
Factorized diffusion with Transformer depth increased from 12 to 24 layers for the scaled model. FACodec separates content, prosody, timbre and acoustic detail.Source for Architecture (opens in a new tab)
Training dataset
Internal dataset with 200,000 hours of speech. Dataset composition and complete language inventory not disclosed.Source for Training dataset (opens in a new tab)
Audio sample rates
16 kHz speech in the reported systemSource for Audio sample rates (opens in a new tab)
Voice controls
Attribute-specific prompts permit timbre, prosody and speech-duration manipulation.Source for Voice controls (opens in a new tab)
Audio codec design
FACodec factorizes content, prosody, acoustic detail and timbre. Public FACodec checkpoints cover the codec component, not the full diffusion synthesis system.Source for Audio codec design (opens in a new tab)

Access & pricing

Prices belong to an endpoint and billing tier. A provider listing does not guarantee access for every account or region.

Microsoft Research (prerecorded samples)

Provider source (opens in a new tab)
API model ID
Not collected

No public API model selector.

Access
Read the paper and listen to prerecorded examples. No user-callable inference endpoint established by the reviewed project.
Regions
Not applicable to prerecorded research samples.

Endpoint pricing has not been collected. Check the provider for applicable rates.

Data & enterprise terms

No hosted customer inference or data-retention contract verified.

Caching

Caching can reuse earlier input processing. Availability, lifetime and billing depend on the endpoint. A cache hit still generates a new response.

01 / INITIAL INPUTProcess & retain

The system processes eligible input and retains reusable state.

02 / LATER REQUESTCheck available state

Reuse depends on matching input, session state and the cache policy.

03 / CACHE HITReuse & generate

Reusing state can reduce repeated work. Any charges follow the billing rules below.

Microsoft Research (prerecorded samples)

Not verified

No public service cache contract verified.

How it works
Not collected
Minimum reusable input
Not collected
Lifetime & refresh
Not collected
How to enable it
Not collected
Usage fields
Not collected
Billing rules
Not collected
Limits & data boundaries
Not collected

No verified cache rate for this endpoint. An empty rate is not a zero charge.

Caching reviewed 14 Oct 2026

What the measurements say

No benchmark observations have been added for this model. We do not turn a vendor description into a performance score.

Latency and throughput depend on the host, request size, reasoning settings and load. There is no measured speed or global usage figure in this record.

The record behind the model

Why it is included

Classification is an evidence-based inference for the original research checkpoint: the authors provide papers and prerecorded samples, but no full original model weights or callable service in the reviewed project materials. The Microsoft Hugging Face account lookup also returns no matching model. This does not classify independent implementations or separately released codec components as closed.

Classification evidence (opens in a new tab)

Lifecycle dates

Research family first published on arXiv5 Mar 2024Source (opens in a new tab)

Sources reviewed