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Llama-4-Maverick-17B-128E-Instruct-FP8
Meta · llama-4-maverick-17b-128e-instruct-fp8
Open multimodal Llama model for strong reasoning and fast responses
Starting price
0
per million tokens
Billing
Pay as you go
Service status
Active
Released
2025
About Llama-4-Maverick-17B-128E-Instruct-FP8
Open multimodal Llama model for strong reasoning and fast responses
Llama-4-Maverick-17B-128E-Instruct-FP8 pricing
Input
0
Output
0
Cache (read)
0
Cache (write)
0
same as input
Model id
Provider
Context window
Max output tokens
Inputs
Outputs
Status
Released
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Sample code and API for Llama-4-Maverick-17B-128E-Instruct-FP8
Point the base URL at CupAI and use your own API key; the rest of the request stays exactly as it is in any compatible client.
curl 'https://api.cupai.ir/v1/chat/completions' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer $CUPAI_API_KEY' \
-d '{
"model": "llama-4-maverick-17b-128e-instruct-fp8",
"messages": [
{
"role": "user",
"content": "Hello!"
}
]
}'Replace CUPAI_API_KEY with your own key.
Create an API key
Capabilities
Capabilities supported by this model's API.
text-to-text
image-to-text
Frequently asked questions about Llama-4-Maverick-17B-128E-Instruct-FP8
- How is usage of Llama-4-Maverick-17B-128E-Instruct-FP8 billed?
- By the input and output tokens of each request. The rate for each part is in the pricing table on this page, and the amount is deducted from your wallet.
- How do I connect to Llama-4-Maverick-17B-128E-Instruct-FP8?
- Point the base URL at CupAI, put your API key in the request header, and send the model id in the request body. Ready-made samples are on this page.
- How do payments work?
- Payments are in Toman and need no foreign credit card. Credit you buy can be spent on any available model.
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How model pricing works
Every AI model strikes a different balance between speed, answer quality and cost. Flagship models suit complex reasoning, long-document analysis and precise code generation, while lighter models cost considerably less for summarising, classification and short answers. The list above shows each model's rate broken down by input token, output token and cache, so you can estimate the cost of your workload before you start.
A token is the smallest unit of text a model processes; roughly speaking a thousand tokens is about 750 English words. The cost of a request is the sum of its input and output tokens, so shortening your prompt and capping the response length reduces cost directly. Some models have a second price tier for very long inputs, which reprices the entire request once it crosses a stated threshold.