Model Cost Profile

Meta: Llama 4 Maverick

Developer: meta-llama

Pricing updated Mar 11, 2026

Input rank: #116Output rank: #133

Live Pricing

Input: $0.1500

Output: $0.6000

Pricing via OpenRouter API ยท Last synced Mar 11, 2026

Meta: Llama 4 Maverick offers a substantial context window of 1,048,576 tokens, making it suitable for applications requiring extensive data processing, such as document summarization and complex conversational agents. With an input price of $0.15 per 1 million tokens and an output price of $0.60 per 1 million tokens, teams can effectively budget for high-volume usage while optimizing their operational costs. This model is ideal for organizations that need to analyze large datasets or generate detailed content without sacrificing performance or incurring excessive expenses.

๐Ÿ‘ Vision๐Ÿ”ง Tool Calling๐Ÿ“‹ Structured Output

Context Window

1,048,576

Tokens

Input Price / 1M

$0.1500

Prompt tokens

Output Price / 1M

$0.6000

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Meta: Llama 4 Maverick Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 11
$0.1500$0.3750$0.6000Mar 7Mar 8Mar 9Mar 10Mar 11

Current Input / 1M

$0.1500

Current Output / 1M

$0.6000

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FAQ

Common pricing and benchmark questions for Meta: Llama 4 Maverick.

How much does Meta: Llama 4 Maverick cost per 1M input tokens?

Meta: Llama 4 Maverick input pricing is $0.1500 per 1M tokens based on the latest synced provider data.

How much does Meta: Llama 4 Maverick cost per 1M output tokens?

Meta: Llama 4 Maverick output pricing is $0.6000 per 1M tokens based on the latest synced provider data.

What context window does Meta: Llama 4 Maverick support?

Meta: Llama 4 Maverick supports a context window of 1,048,576 tokens.

How can I compare Meta: Llama 4 Maverick with cheaper alternatives?

Use the comparison links on this page to open direct model-vs-model pricing and benchmark pages, then evaluate monthly spend projections for your workload.