// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "google/gemma-3-12b-it"
}).then(response => {
document.body.innerHTML = response.message.content;
});
<html>
<body>
<script src="https://js.puter.com/v2/"></script>
<script>
puter.ai.chat("Explain quantum computing in simple terms", {
model: "google/gemma-3-12b-it"
}).then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="google/gemma-3-12b-it",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "google/gemma-3-12b-it",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Gemma 3 12B Instruct is Google's mid-sized open multimodal model supporting text and image input with a 128K token context window. It supports 140+ languages and offers strong performance for single-GPU deployment.
Context Window 131K
tokens
Max Output 131K
tokens
Input Cost $0.04
per million tokens
Output Cost $0.13
per million tokens
Release Date Mar 12, 2025
Output Speed 30
tokens / sec
Latency 23.49s
time to first token
Model Playground
Try Gemma 3 12B instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Gemma 3 12B performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 34.9% |
| Humanity's Last Exam Cross-domain reasoning | 4.8% |
| LiveCodeBench Recent coding problems | 13.7% |
| SciCode Scientific programming | 17.4% |
| MATH-500 Competition math | 85.3% |
| AIME 2024 Advanced math exam | 22.0% |
| AIME 2025 Advanced math exam | 18.3% |
| IFBench Instruction following | 36.7% |
| LCR Long-context reasoning | 6.7% |
| Terminal-Bench Hard Agentic terminal tasks | 0.8% |
| τ²-Bench Tool use / agents | 10.8% |
Scores sourced from Artificial Analysis.
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ChatGemma 4 31B
Gemma 4 31B is a dense multimodal model from Google DeepMind, built on the same research foundation as Gemini 3. It is the most capable model in the Gemma 4 family, accepting text, image, and video input with a 256K-token context window. It delivers strong benchmark results: 89.2% on AIME 2026, 85.2% on MMLU Pro, 80.0% on LiveCodeBench v6, and 84.3% on GPQA Diamond. On the Arena AI text leaderboard, it ranks as the #3 open model globally, outperforming many models with far higher parameter counts. Gemma 4 31B features native function calling trained into the model, configurable chain-of-thought reasoning, and structured JSON output — making it especially well-suited for agentic workflows, coding tasks, and multi-turn tool use. It supports over 140 languages and serves as a strong foundation for fine-tuning.
VideoVeo 3.1 Lite
Veo 3.1 Lite is Google DeepMind's most cost-effective video generation model, built for high-volume applications where per-clip cost is a primary concern. It generates video at the same speed as Veo 3.1 Fast but at less than half the price — starting at $0.05 per second for 720p. The model supports text-to-video and image-to-video with 720p and 1080p output in landscape (16:9) or portrait (9:16), at configurable durations of 4, 6, or 8 seconds. It does not support 4K output, scene extension, or native audio generation — clips are silent by default. Veo 3.1 Lite is ideal for developers building batch video pipelines, social media automation, or interactive tools where cost per generation matters most and audio can be added in post-production.
Frequently Asked Questions
You can access Gemma 3 12B by Google through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add Gemma 3 12B to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.04 |
| Output | $0.13 |
Gemma 3 12B was created by Google and released on Mar 12, 2025.
Gemma 3 12B supports a context window of 131K tokens. For reference, that is roughly equivalent to 262 pages of text.
Gemma 3 12B can generate up to 131K tokens in a single response.
Yes — the Gemma 3 12B API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.
Get started with Puter.js
Add Gemma 3 12B to your app without worrying about API keys or setup.
Read the Docs View Tutorials