Model Cost Profile

Anthropic: Claude Opus 4

Developer: anthropic

Pricing updated Mar 10, 2026

Input rank: #334Output rank: #337

Live Pricing

Input: $15.00

Output: $75.00

Pricing via OpenRouter API ยท Last synced Mar 10, 2026

Anthropic's Claude Opus 4 features an extensive context window of 200,000 tokens, making it ideal for applications requiring deep contextual understanding, such as legal document analysis or long-form content generation. With an input price of $15.00 per million tokens and an output price of $75.00 per million tokens, teams must carefully consider their token usage to manage costs effectively while maximizing the model's capabilities. This pricing structure encourages efficient token management, making it suitable for businesses that require scalable solutions for complex tasks.

๐Ÿ‘ Vision๐Ÿ”ง Tool Calling๐Ÿง  Reasoning

Context Window

200,000

Tokens

Input Price / 1M

$15.00

Prompt tokens

Output Price / 1M

$75.00

Completion tokens

Intelligence (MMLU)

Benchmark Pending

Massive Multitask Language Understanding

Price History

Anthropic: Claude Opus 4 Pricing Trend

Input / 1M tokens0.0%Output / 1M tokens0.0%
Mar 7 โ€” Mar 10
$15.00$45.00$75.00Mar 7Mar 8Mar 9Mar 10

Current Input / 1M

$15.00

Current Output / 1M

$75.00

Cheaper Alternatives to Compare

Quick links for cost-down decisions before production rollout.

FAQ

Common pricing and benchmark questions for Anthropic: Claude Opus 4.

How much does Anthropic: Claude Opus 4 cost per 1M input tokens?

Anthropic: Claude Opus 4 input pricing is $15.00 per 1M tokens based on the latest synced provider data.

How much does Anthropic: Claude Opus 4 cost per 1M output tokens?

Anthropic: Claude Opus 4 output pricing is $75.00 per 1M tokens based on the latest synced provider data.

What context window does Anthropic: Claude Opus 4 support?

Anthropic: Claude Opus 4 supports a context window of 200,000 tokens.

How can I compare Anthropic: Claude Opus 4 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.