Google’s largest open Gemma: a 31-billion-parameter model that reads images and video, under Apache 2.0. Priced in Indian rupees for teams in India, on the same key as every other model.
In Indian rupees, the currency your card is charged in, with the published US dollar rate beside each.
For scale: 1,000 requests of about 3,000 tokens in and 1,000 out cost ₹104.47 — a long prompt and a page of answer each. Every rate is published and stays the same from one request to the next. See every model.
Prices are our published US dollar rates converted at ₹98.00 to the dollar, our rate for October — the same rate your card is charged.
Gemma 4 31B is the biggest model in Google’s open Gemma family, built from the same research as Gemini 3. It is the first Gemma released under the standard Apache 2.0 licence rather than Google’s own terms, and at launch it ranked third among open models on the LMArena text leaderboard. Google’s model card reports 85.2% on MMLU-Pro and 84.3% on GPQA Diamond.
It reads images and video as well as text, with a 256K-token context, and thinks before answering when you switch that on. As a dense 31B model it is small next to the trillion-parameter open models, which shows on long, hard agent tasks — but it is quick and inexpensive for document and image work.
gemma-4-31b-itRoar AI provides access to Gemma 4 31B through the Roar AI gateway, charged in Indian rupees on one bill with every other model. Requests from India go through our gateway in Bangalore. Developers can use Gemma 4 31B alongside other supported models without a separate integration for every provider.
Use the OpenAI SDK you already have — point it at Roar AI and name the model. Read the docs.
from openai import OpenAI
client = OpenAI(base_url="https://api.roar-ai.com/v1", api_key="roar_live_…")
reply = client.chat.completions.create(
model="gemma-4-31b-it",
messages=[{"role": "user", "content": "Summarise this contract in plain English."}],
)Requests to Gemma 4 31B are processed on international infrastructure, outside India. The model directory says where each model is processed.
Input is ₹17.84 per 1M tokens; output is ₹50.96 per 1M tokens. For scale, 1,000 requests of about 3,000 tokens in and 1,000 out cost ₹104.47. Prices are our published US dollar rates converted at ₹98.00 to the dollar, our rate for October — the same rate your card is charged. The rate is published and does not change from one request to the next.
Its weights are open under the Apache 2.0 licence, so you could run it yourself. Through Roar AI you call it like any other model, with no servers to manage.
Sign up, get a key and call it with the SDK you already use. Pay in your local currency, on one bill.