Compare inference costs across GPT-5, Claude 4.5, Gemini 3, and more.
Now with agentic loops, caching, and reasoning tokens
In 2026, most AI applications use multi-step "agentic loops" rather than single prompts. Calculate costs for workflows like: "5 research steps + 1 summary step = 6 total steps."
Modern APIs (Anthropic, Gemini, OpenAI) offer context caching that reduces input costs by up to 90% for repeated data. Set your cache hit rate to see potential savings.
Reasoning models (like OpenAI's o-series) "think" before responding. These "thinking tokens" cost extra money and are often missed by older calculators. Enable reasoning to see the true cost.
Enable context caching to save up to 90% on repeated inputs
| Model | Input Price | Output Price | Context | Total Cost | vs. Lowest |
|---|---|---|---|---|---|
Claude 4 OpusAnthropic | $15.00/1M | $75.00/1M | 200.0K | $0.9000 | Lowest |
Copy-paste code to integrate Claude 4 Opus into your application
import anthropic
client = anthropic.Anthropic(api_key="your-api-key")
message = client.messages.create(
model="claude-4-opus",
max_tokens=2000,
messages=[
{"role": "user", "content": "Your prompt here"}
]
)
print(message.content)💡 Replace "your-api-key" with your actual API key. Adjust tokens and parameters as needed.
Calculate accurate API costs for Claude 4 Opus (Anthropic). Estimate token pricing, input/output costs, context caching savings, and total expenses for your AI application.
$15.00/1M tokens
$75.00/1M tokens
$1.50/1M tokens
200,000
tokens supported
Claude 4 Opus is ideal for applications requiring high throughput. With input pricing at $15.00 per 1M tokens, it's cost-effective for processing large volumes of text, images, making it suitable for content generation, data processing, and automated workflows.
With a context window of 200,000 tokens, Claude 4 Opus excels at tasks requiring extensive context. Perfect for document analysis, long-form content generation, code review, and multi-turn conversations that span thousands of tokens.
Leverage context caching at $1.50 per 1M tokens to reduce costs for repeated inputs. Ideal for applications with recurring prompts, template-based generation, and batch processing where input context can be reused.
Enable context caching to reduce input costs from $15.00 to $1.50 per 1M tokens for repeated contexts.
Shorter, more focused prompts reduce token usage. Use system messages effectively and avoid redundant context to minimize input costs.
Track your input/output token ratios. If output costs are high, consider using Claude 4 Opusfor initial processing and cheaper models for follow-up tasks.
Costs vary based on input/output tokens, caching usage, and additional features. Input tokens cost $15.00 per 1M tokens, while output tokens cost $75.00per 1M tokens. Use the calculator above to estimate costs for your specific use case.
Claude 4 Opus supports up to 200,000 tokens in a single context window. This allows for processing of long documents, extensive conversations, and complex multi-step tasks without truncation.
Context caching allows you to reuse input context across multiple requests, reducing costs from $15.00 to $1.50 per 1M tokens. This is ideal for applications with repeated system prompts, templates, or shared context.
Yes! Claude 4 Opus provides a standard API that can be integrated into any application. Check the developer code snippet below the calculator for Python and Node.js integration examples.