// 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 | 26.7% |
| 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 | 67.0% |
| 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 4.6
Grok 4.6 is xAI's frontier model for long-running agents and interactive, visual development work, built on the same 1.5-trillion-parameter V9 foundation as Grok 4.5 with additional supervised fine-tuning and reinforcement learning. It matches GPT-5.6 Sol on the Artificial Analysis Intelligence Index (both score 61) and leads on CursorBench v3.2 at 69.9%, with gains over Grok 4.5 across coding, research, and agentic benchmarks. xAI highlights it for vulnerability patching, engineering design work, and turning a rough product idea into a working first version, with improved self-testing on longer tasks. The model accepts text and image input with text-only output, a 500,000 token context window, and no output token limit. Reasoning effort is configurable across four levels (low, medium, high, xhigh), and it supports function calling, web search, X search, and code execution. At $2 per million input tokens and $6 per million output tokens, it costs the same as Grok 4.5.
ChatGrok 4.5
Grok 4.5 is xAI's flagship mixture-of-experts model, trained jointly with Cursor on trillions of tokens of real coding sessions alongside STEM, research, and knowledge-work data. Elon Musk described it as an Opus-class model, faster and more token-efficient at a lower cost than comparable frontier models. It is tuned for coding, including Rust and C/C++, and for multi-step agentic workflows. It also handles finance and legal work, and can build multi-sheet Excel models with live web research, design diagrams in PowerPoint, and write structured documents in Word. Reasoning effort is configurable as low, medium, or high, with high as the default. The model accepts text and image input, supports a 500,000 token context window, and includes native tool calling. At $2 per million input tokens and $6 per million output tokens, it suits developers building coding agents and knowledge-work tools who need frontier-level capability without paying Opus-class pricing.
ImageGrok 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.
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 34.1 on the Artificial Analysis Intelligence Index, outperforming 78% 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