Text model

Grok 4.7

grok-4.7

grok-4.7 is available at grok-4.7. Below: prices per channel, specifications and request examples.

Prices per channel

ChannelInput, per 1MOutput, per 1MCache, per 1M
Auto · default
grok-4.7
$0.0744$0.223$0.0186
Channel 20
grok-4.7:c20
$0.0744$0.223$0.0186

Prices per 1M tokens. You pay for what you use. Pick a channel with a suffix: grok-4.7:c20; without one you get the default channel.

Specifications

Context window
480,000 tokens
Max output tokens
32,768 tokens
Image input
no
Reasoning
yes
Anthropic format (/v1/messages)
no
Data in Russia
no

Request example

Create a key in the dashboard. Streaming works too: add "stream": true.

curl
curl https://demo-en.alexshkarupa.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "grok-4.7", "messages": [{"role": "user", "content": "Hello!"}]}'
Python
from openai import OpenAI

client = OpenAI(base_url="https://demo-en.alexshkarupa.com/v1", api_key="YOUR_KEY")
reply = client.chat.completions.create(
    model="grok-4.7",
    messages=[{"role": "user", "content": "Hello!"}],
)
print(reply.choices[0].message.content)

Questions and answers

How much does grok-4.7 cost?

Input is $0.0744 per 1M tokens, output $0.223 per 1M. You are charged for the tokens actually used, so a single request costs a fraction of a cent. Your balance and spending are in the dashboard.

What is the context window of grok-4.7?

Up to 480,000 input tokens and up to 32,768 output tokens.

How do I call grok-4.7?

Set the base URL to https://demo-en.alexshkarupa.com/v1 and use "grok-4.7" in the model field of any OpenAI-compatible client. curl and Python examples are on this page.

How do channels differ?

Channels are independent routes to the same model at different prices. Without a suffix a request takes the default channel; to pin a channel add its number: grok-4.7:c20. A pinned channel never fails over silently: if it is unavailable, the request returns an error.

Is cached input cheaper?

Repeated context is billed at the cache price — $0.0186 per 1M tokens instead of $0.0744.

Does it support reasoning?

Yes, the model supports a reasoning mode; its depth is set by a request parameter.

Other models

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