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Model infoModelsSnapshot: 15 Oct 2026

Microsoft AI / VALL-E 2

VALL-E 2

Private speech-synthesis research model with repetition-aware sampling and grouped codec prediction. Published quality findings are scoped to LibriSpeech and VCTK experiments.

restrictedClosed weightsText-to-speech
Official documentation (opens in a new tab)Reviewed 14 Oct 2026
15 of 28 specification fields collected
Audio sample rates24 kHz audio reconstructionSee specification notes below
Languages1 listedFull language list in specifications
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 product contract verified for this research checkpoint.

Maximum input tokens
Not collected

No public product contract verified for this research checkpoint.

Maximum output
Not collected

No public product contract verified for this research checkpoint.

Reasoning
Not collected

No public product contract verified for this research checkpoint.

Tool calling
Not collected

No public product contract verified for this research checkpoint.

Structured output
Not collected

No public product contract verified for this research checkpoint.

Streaming
Not collected

No public product contract verified for this research checkpoint.

Batch processing
Not collected

No public product contract verified for this research checkpoint.

Fine-tuning
Not collected

No public product contract verified for this research checkpoint.

Parameters
Not collected

No public product contract verified for this research checkpoint.

Knowledge cutoff
Not collected

No public product contract verified for this research checkpoint.

Release date
Not collected

No public product contract verified for this research checkpoint.

Context caching
Not collected

No public product contract verified for this research checkpoint.

Languages
EnglishSource for Languages (opens in a new tab)

Language of the documented trained checkpoint, not a claim of universal language coverage.

Endpoint availability
Private research checkpoint; public samples and paper only. No public inference access planned in the reviewed project statement.Source for Endpoint availability (opens in a new tab)
Voice cloning
SupportedSource for Voice cloning (opens in a new tab)

Research demonstration of synthesis in a reference speaker’s voice; not a customer-accessible voice-cloning product.

Reference audio
Three-second prefixes for continuation; project examples also use 3-, 5- and 10-second reference prompts.Source for Reference audio (opens in a new tab)

Experimental prompt lengths, not supported API limits.

Research publication
2024-06-08Source for Research publication (opens in a new tab)

First arXiv disclosure of the research family. The reviewed paper may contain later revisions; this is not a commercial release date or a separate variant announcement date.

Architecture
Autoregressive first-code prediction with non-autoregressive prediction of remaining codebooks; repetition-aware sampling and grouped code modeling.Source for Architecture (opens in a new tab)
Training dataset
Libriheavy: approximately 50,000 hours of English speech from around 7,000 speakers.Source for Training dataset (opens in a new tab)
Training hardware
16 NVIDIA Tesla V100 32GB GPUs for AR and NAR model training.Source for Training hardware (opens in a new tab)
Audio sample rates
24 kHz audio reconstructionSource for Audio sample rates (opens in a new tab)
Audio codec design
EnCodec at 6 kbps with Vocos decoder; BPE text tokenization.Source for Audio codec design (opens in a new tab)
Inference modes
Zero-shot cross-sentence synthesis, Speech continuationSource for Inference modes (opens in a new tab)
Research controls
Four trained AR configurations use group sizes 1, 2, 4 and 8 and share one NAR model.Source for Research controls (opens in a new tab)
Research configurations
AR group size 1, AR group size 2, AR group size 4, AR group size 8Source for Research configurations (opens in a new tab)

Four separately trained AR configurations sharing one NAR model, per Section 4.1.1. They are research configurations within this family, not four commercial model releases.

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 inference endpoint or model selector.

Access
Read the paper and listen to prerecorded research samples. This is not an interactive model service and does not accept inference requests.
Regions
Not applicable to prerecorded research samples.

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

Data & enterprise terms

No customer inference service or data-processing policy is established by the research demo.

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 endpoint cache contract for this private research model.

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

The original Microsoft research project explicitly states that it has no plans to provide public access or incorporate this model into a product. The reviewed original project and paper provide no full-model weight release. Open codec/vocoder components and third-party reproductions do not establish access to these original checkpoints.

Classification evidence (opens in a new tab)

Lifecycle dates

Research family first published on arXiv8 Jun 2024Source (opens in a new tab)

Sources reviewed