Gemma 4 31B on Sarvam AI

Gemma 4 31B is a 31B-parameter instruction-tuned model for text and image understanding. It accepts text and inline images with a 131,072-token context window.

Gemma 4 31B is available in beta and is not specifically tuned for Indian languages. Access is granted per API key — contact us to request access.

At a glance


Model ID	`gemma4`
Best for	Image captioning, classification, and visual question answering
Context window	131,072 tokens
Input → output	Text and images → text
Reasoning	No; answers are returned directly
Tool calling	Supported
Log probabilities	Supported on Chat Completion V2 (`logprobs` / `top_logprobs`)
APIs	`POST /v2/chat/completions` and `POST /v2/responses`
Pricing	₹36.6 input · ₹13.73 cached input · ₹91.5 output per 1M tokens (Pricing)

Key capabilities

Image understanding

Caption, classify, and answer questions about images supplied as base64 data URIs.

Direct answers

Receive the answer without a separate reasoning pass.

Tool calling

Use OpenAI-compatible tools and tool_choice for agentic workflows.

Streaming

Receive answer deltas as server-sent events.

Quickstart

The examples send a local image as a base64 data URI. Remote image URLs are not supported.

import base64
from sarvamai import SarvamAI
client = SarvamAI(api_subscription_key="YOUR_SARVAM_API_KEY")
with open("chart.png", "rb") as image:
    encoded = base64.b64encode(image.read()).decode("utf-8")
response = client.chat.completions_v2(
    model="gemma4",
    messages=[
        {
            "role": "user",
            "content": [
                {"type": "text", "text": "What trend does this chart show?"},
                {
                    "type": "image_url",
                    "image_url": {"url": f"data:image/png;base64,{encoded}"},
                },
            ],
        }
    ],
    temperature=1,
    top_p=0.95,
    max_tokens=500,
)
print(response.choices[0].message.content)

API reference

Call POST /v2/chat/completions or POST /v2/responses with model: "gemma4". Request fields (logprobs, stream, tools, image parts, and the rest) are defined in those API references — not duplicated on this model page.

Images must be base64 data URIs in image_url content parts (remote URLs are rejected).

Limits and errors

Area	Limit or condition	API response	Recommended action
Context	Prompt tokens plus `max_tokens` exceed 131,072	`422 unprocessable_entity_error`	Shorten the prompt, send fewer images, or reduce `max_tokens`.
Output	`max_tokens` exceeds 131,072	`400 invalid_request_error`	Set `max_tokens` within the context window.
Request size	Request body exceeds 10 MB	`413 invalid_request_error`	Reduce the request body; base64-encoded images count toward the limit.
Image URL	An `image_url` uses an `http(s)` URL	`400 invalid_request_error`	Inline the image as a base64 data URI.
Structured output	`response_format` is combined with a JSON instruction in the prompt	`200` with whitespace output and `finish_reason: "length"`	Remove the duplicate JSON instruction from the prompt.
Tools	The tool schema is invalid	`400 invalid_request_error`	Check the schema requirements in Chat Completion V2.
Authentication	API key is missing or invalid	`403 invalid_api_key_error`	Check the `api-subscription-key` header.
Access	API key does not have beta access	`400 invalid_request_error`	Request beta access.
Model	Model ID is unknown or unavailable	`404 not_found_error`	Confirm the ID with `GET /v2/models`.
Quota	No credits remain	`402 insufficient_quota_error`	Add credits in the dashboard.
Rate limit	Request or concurrency limit is exceeded	`429 rate_limit_exceeded_error`	Back off and retry.
Availability	Model remains overloaded after retries	`503 model_overloaded`	Retry later.