Sarvam AI: Sarvam-Translate

Overview

Sarvam AI's open-weights translation model for English and all 22 scheduled Indian languages, built with AI4Bharat on Gemma 3 4B IT, for formal, document-level text up to 8K tokens. The open checkpoint translates only between English and an Indian language, in either direction. GPL 3.0 licence.

Provider

Sarvam AI

Modality

Text

Input

text

Output

text

Weights

Open weights

Tags

open-weights, translation, indian-languages

Docs

Provider documentation

Data policy

Prompts go to

Sarvam AI through its API, on its managed environment in Microsoft Azure's Central India region. A copy of the open weights you host sends nothing to Sarvam.

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 Sarvam-Translate can be deployed, bought and reached through Safeguard.

Deployment

Public cloudPrivate cloudOn-premAir-gapped

Procurement

Not published yet

Inference regions

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

On-prem and air-gapped deployments run wherever you install them.

Pricing

Notes

Through Sarvam's API: INR 20 per 10,000 characters (Sarvam Translate V1), up to 2,000 characters per request. 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/sarvam-translate",
    messages=[{"role": "user", "content": "Hello"}],
)
print(response.choices[0].message.content)

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