// 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
Output Speed 44
tokens / sec
Latency 17.09s
time to first token
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 4.3
Grok 4.3 is xAI's latest flagship reasoning model, designed for agentic workflows, instruction following, and tasks demanding high factual accuracy. It accepts text and image inputs with always-on reasoning that cannot be disabled. The model supports a 1 million token context window with no output token limit, making it well suited for long-document analysis and multi-step agent tasks. Priced at $1.25 per million input tokens and $2.50 per million output tokens, it delivers improved cost-efficiency over its predecessor Grok 4.20 — scoring higher on the Artificial Analysis Intelligence Index while costing roughly 20% less to run. Grok 4.3 showed a major jump in real-world agentic task performance, gaining over 300 Elo points on GDPval-AA versus Grok 4.20. It also scores 98% on τ²-Bench Telecom and 81% on IFBench. A strong pick for developers building cost-sensitive agent systems that need reliable tool use and instruction adherence.
ChatGrok 4.20
Grok 4.20 is xAI's flagship large language model, offering a rare combination of low hallucination rates and high throughput at competitive pricing. It achieved a record 78% non-hallucination rate on the Artificial Analysis Omniscience benchmark — the highest of any model tested — making it a strong choice for applications where factual reliability matters more than peak reasoning scores. It scored 78.5% on GPQA Diamond and 87.3% on MATH-500. The model supports a 2M-token context window, text and image inputs, parallel function calling, structured outputs, and built-in web search. Reasoning can be toggled on or off per request via API parameter. At $2 per million input tokens and $6 per million output tokens, it's one of the most affordable frontier models available, with output speeds exceeding 230 tokens per second.
ChatGrok 4.20 Multi-Agent
Grok 4.20 Multi-Agent is a variant of xAI's Grok 4.20 purpose-built for orchestrating multiple AI agents that collaborate on complex, multi-step tasks in real time. Rather than relying on a single inference pass, it coordinates parallel agents that independently search, analyze, and cross-reference information before synthesizing a final response. At low or medium reasoning effort it runs 4 agents; at high or extra-high effort it scales to 16. It scored a 68.7 agentic index on Artificial Analysis — among the highest available. The model shares Grok 4.20's 2M-token context window and natively supports web search, X search, and tool orchestration. It generates up to 2M output tokens per response, making it well suited for deep research workflows, multi-source analysis, and long-running agent pipelines.
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 41.5 on the Artificial Analysis Intelligence Index, outperforming 86% of tracked models. On coding, it scores 40.5 (outperforms 89% of 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