Sarvam AI: Bulbul v3

Overview

Sarvam AI's stable text-to-speech model and the API default: more than 30 named voices for 10 Indian languages and English, pace control, sample rates up to 48 kHz and up to 2,500 characters per request, also offered for self-hosting on Amazon SageMaker.

Provider

Sarvam AI

Modality

Speech

Input

text

Output

audio

Weights

Closed

Distillable

NoLicence or terms, checked October 9, 2026.

Tags

text-to-speech, audio, indian-languages

Docs

Provider documentation

Data policy

Prompts go to

Sarvam AI, on its managed environment in Microsoft Azure's Central India region. Self-hosted on Amazon SageMaker in your own AWS account, audio and documents stay in your account.

Retention

Sarvam keeps Model API data until the workspace Owner sets a retention period, and No retention (0 days) is available for Model APIs. Sarvam's terms let it train its own models on inputs and outputs as its Privacy Policy and the law allow, with consent where required, and its Trust Center says one customer's data never trains models for another customer.

Zero data retention

Available

Region

India: Sarvam's managed production environment runs in Microsoft Azure's Central India region.

Policy

Sarvam AI data policy

Summarised from the provider's published terms. The provider's own policy is what applies.

Where you can run it

How Bulbul v3 can be deployed, bought and reached through Safeguard.

Deployment

Public cloudPrivate cloud

Procurement

Not published yet

Inference regions

🇮🇳IndiaCloud provider's availability page, checked October 9, 2026.

Closed weights stay with the provider, so this model runs in the provider's cloud, never on-prem or air-gapped.

Pricing

Notes

INR 30 per 10,000 characters, rounded to the nearest character. Prices are in Indian rupees only, so no US dollar price is shown.

Source

Sarvam AI pricing , last verified October 9, 2026

No markup on model usage: you pay the provider's list price.

API

OpenAI-compatible. Your API key and access to this model are set up for your workspace when you choose Use with Safeguard.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.safeguard.sh/gpt/v1",
    api_key="SAFEGUARD_API_KEY",
)

response = client.chat.completions.create(
    model="sarvam/bulbul-v3",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

Base URL https://api.safeguard.sh/gpt/v1, model sarvam/bulbul-v3.