// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms", {
model: "x-ai/grok-4-0709"
}).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: "x-ai/grok-4-0709"
}).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="x-ai/grok-4-0709",
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": "x-ai/grok-4-0709",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
Model Card
Grok 4 0709 is the July 9, 2025 snapshot of xAI's flagship reasoning model, trained with reinforcement learning to use tools like a code interpreter and web browsing. It features a 256K context window, native tool use, parallel tool calling, and support for both image and text inputs.
Context Window 256K
tokens
Max Output 256K
tokens
Input Cost $3
per million tokens
Output Cost $15
per million tokens
Input text, image
modalities
Tool Use Yes
Knowledge Cutoff Jul 2025
Release Date Jul 9, 2025
Model Playground
Try Grok 4 0709 instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How Grok 4 0709 performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 87.7% |
| Humanity's Last Exam Cross-domain reasoning | 23.9% |
| LiveCodeBench Recent coding problems | 81.9% |
| SciCode Scientific programming | 45.7% |
| MATH-500 Competition math | 99.0% |
| AIME 2024 Advanced math exam | 94.3% |
| AIME 2025 Advanced math exam | 92.7% |
| IFBench Instruction following | 53.7% |
| LCR Long-context reasoning | 68.0% |
| Terminal-Bench Hard Agentic terminal tasks | 37.9% |
| τ²-Bench Tool use / agents | 74.9% |
Scores sourced from Artificial Analysis.
Find other xAI models →
Grok Imagine Image
Grok Imagine Image is xAI's standard text-to-image generation model, built on Aurora — an autoregressive Mixture-of-Experts architecture trained on billions of text-image pairs. It accepts text prompts and optional reference images as input, producing up to 10 images per request at 1K (1024×1024) or 2K (2048×2048) resolution across 13 aspect ratios. Output formats include JPEG, PNG, and WebP. The model is noted for strong instruction following, handling style transfer, object addition or removal, and multi-reference composition through natural language alone. It generates images quickly, making it practical for high-volume pipelines. Best suited for product mockups, marketing visuals, social media graphics, and concept art prototyping where speed and prompt adherence matter. A higher-quality variant, Grok Imagine Image Pro, is available when output fidelity is the priority.
ImageGrok Imagine Image (Quality)
Grok Imagine Image (Quality) is xAI's high-fidelity text-to-image generation model, built on the Aurora autoregressive Mixture-of-Experts architecture rather than a diffusion backbone. It targets applications where output quality is the priority over speed — delivering more natural lighting, richer textures, and cinematic consistency compared to standard-tier image models. Text rendering in generated images is notably legible across multiple languages, addressing a historically weak area for generative image models. The API supports 1K and 2K resolutions, 13 aspect ratios, and JPEG, PNG, and WebP outputs. Up to four image candidates can be generated per request. At $0.05 per image, it is well suited for product visuals, marketing assets, brand imagery, and creative workflows that require production-ready quality.
ChatGrok Build 0.1
Grok Build 0.1 is xAI's fast coding model trained specifically for agentic software engineering workflows. Released in May 2026 and currently in early access, it is purpose-built for interactive coding agents, tool use, and multi-step development tasks rather than general-purpose conversation. The model accepts text and image inputs and produces text output, with a 256,000-token context window. It supports function calling, structured outputs, and built-in reasoning that is always active, enabling it to think through problems before responding. Developers building AI coding agents, automated code review pipelines, or multi-step development tools will find it a strong fit. At $1/M input and $2/M output tokens, it offers an accessible price point for agentic, high-throughput use cases.
Frequently Asked Questions
You can access Grok 4 0709 by xAI 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 Grok 4 0709 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 | $3 |
| Output | $15 |
Grok 4 0709 was created by xAI and released on Jul 9, 2025.
Grok 4 0709 supports a context window of 256K tokens. For reference, that is roughly equivalent to 512 pages of text.
Grok 4 0709 can generate up to 256K tokens in a single response.
Grok 4 0709 has a knowledge cutoff date of Jul 2025. This means the model was trained on data available up to that date.
Grok 4 0709 accepts the following input types: text, image. It produces: text.
Yes, Grok 4 0709 supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
Grok 4 0709 scores 33.3 on the Artificial Analysis Intelligence Index, outperforming 84% of tracked models. On math, it scores 92.7 (outperforms 94% of models).
Yes — the Grok 4 0709 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 Grok 4 0709 to your app without worrying about API keys or setup.
Read the Docs View Tutorials