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Gemma 3 4B IT

Google · Text · Context 128K · max output 8K tokens

gemma-3-4b-it Try

Pricing

Per 1 million tokens
MarkasAIVendor list price
InputRp 765Rp 895
OutputRp 1.529Rp 1.789
CacheRp 765
Cache writeRp 765

MarkasAI sale prices in Rupiah, read from the same catalog as GET /v1/models. Prices can change and apply to later requests.

Specifications

Model ID
gemma-3-4b-it
Provider
Google
Type
Text
Endpoint
POST /v1/chat/completions
Context window
128,000 tokens
Output limit per request
8,000 tokens

About this model

Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages, and offers improved math, reasoning, and chat capabilities,...

Quoted from the provider's public catalog, in English.

Call example

curl https://api.markas.ai.id/v1/chat/completions \
  -H "Authorization: Bearer $MARKASAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gemma-3-4b-it",
    "messages": [{"role": "user", "content": "What is an API?"}],
    "max_tokens": 300
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://api.markas.ai.id/v1", api_key=os.environ["MARKASAI_API_KEY"])

resp = client.chat.completions.create(
    model="gemma-3-4b-it",
    messages=[{"role": "user", "content": "What is an API?"}],
    max_tokens=300,
)
print(resp.choices[0].message.content)
import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.markas.ai.id/v1", apiKey: process.env.MARKASAI_API_KEY });

const resp = await client.chat.completions.create({
  model: "gemma-3-4b-it",
  messages: [{ role: "user", content: "What is an API?" }],
  max_tokens: 300,
});
console.log(resp.choices[0].message.content);

Keep your API key in the MARKASAI_API_KEY environment variable. Read the endpoint docs

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