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Claude 4 Pricing Calculator

Instantly calculate your Claude 4 costs, just enter input, output, and call volume. Then explore how it compares to Claude Sonnet 4, Opus 4.
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Claude 4 Cost – Compare Opus 4 & Sonnet 4

Your complete guide to understanding, estimating, and optimizing Claude 4 API usage.

If you’re here, I’m guessing one of three things is true:

  • You’re planning to use Claude 4 (Opus 4 or Sonnet 4) for a project and want to avoid bill shock.
  • You’re comparing Claude to GPT-4.1, GPT-4o, Gemini, or other large language models, and you want to see how the cost lines up with performance.
  • You’re already using Claude and your monthly API bill keeps creeping higher — you want to cut costs without cutting results.

I’ve been in all three situations.
I’ve priced Claude for:

This page gives you all of that in one place.

Quick Claude 4 Facts — 2025 Edition

Claude 4 is actually two models:

  • Claude Opus 4 → Anthropic’s most powerful model, designed for complex coding, deep reasoning, and long-running tasks.
  • Claude Sonnet 4 → A slightly smaller, more affordable model that still delivers state-of-the-art coding and reasoning.
Claude 4 Pricing Overview

Claude 4 Pricing Overview

USD per 1M tokens. Last updated 2025.

Model Input Price (per 1M) Context Window Output Price (per 1M) Best For
Claude Opus 4 $15 200K tokens $75 coding AI agents deep research
Claude Sonnet 4 $3 200K tokens $15 high-volume strong coding cost-performance

▶️ Pro Tip:

  • Prompt caching = up to 90% cheaper if you reuse the same prompt or system message.
  • Batch processing = ~50% cheaper for background jobs.

In other words, forty in-depth customer chats cost less than a latte—and you knew the budget impact before a single merge-request.

Understanding Tokens

If you’ve never worked with LLM pricing before, here’s the simplest way to think about it:

  • Input tokens = what you send to Claude (your prompt, context, and instructions).
  • Output tokens = what Claude sends back to you (the reply).
  • Tokens are chunks of text — usually smaller than a word.

💡 Quick conversions:

  • 1 word ≈ 1.3 tokens
  • 1 token ≈ 4 characters (including spaces)

Example: "Hello world" = 2 words ≈ 2.6 tokens ≈ 11 characters.

How the Claude 4 Pricing Calculator Works

We created this tool to mimic how real people think, rather than how billing documents are typically written.

Step 1 — Pick your unit

Claude 4 pricing calculator input fields for token counts, API calls, and unit type selection, allowing cost estimation by tokens, words, or characters.

You can tell the calculator your usage in:

  • Tokens (best for devs tracking usage in code)
  • Words (best for writers, marketers, or anyone thinking in prose)
  • Characters (best for UI limits, SMS, tweets, etc.)

Step 2 — Fill in your three numbers

  • Input size → How long is your prompt or the data you send?
  • Output size → How long do you expect Claude’s reply to be?
  • Number of calls → How many times will you send a request?

Step 3 — Get your cost instantly

Claude 4 pricing calculator results table showing cost breakdowns for Opus 4, Sonnet 4, and other Anthropic models, including input/output token rates, per-call cost, and total cost.

The calculator updates live and shows:

  • Cost per call
  • Total cost for all calls
  • Side-by-side comparison for Opus 4, Sonnet 4, and other models

Official Claude 4 Pricing (2025)

Source: Anthropic launch post

Token Type Opus 4 Sonnet 4 Why It Matters
Input $15.00 $3.00 Price for sending prompts to the model
Cached Input Up to 90% cheaper Up to 90% cheaper If a prompt repeats, it costs far less
Output $75.00 $15.00 Price for the model’s reply

Real-World Examples

Let’s walk through three real cases I’ve actually seen.

Example 1 — Customer Support Bot (Sonnet 4)

If you implement a chatbot that answers customer emails using your help docs.

  • Input per chat: 600 words (customer message + chat history)
  • Output per chat: 800 words (answer + follow-up)
  • Calls: 15 per day × 30 days = 450 calls/month

Token math:

  • Input: 600 × 1.3 = 780 tokens × 450 = 351,000 tokens (0.351M)
  • Output: 800 × 1.3 = 1,040 tokens × 450 = 468,000 tokens (0.468M)

Cost:

  • Input: 0.351 × $3 = $1.05
  • Output: 0.468 × $15 = $7.02
  • Total monthly: $8.07

With prompt caching for the system prompt → drops to about $6/month.

Example 2 — Large Code Refactor (Opus 4)

You can use Claude to help refactor multiple files in a legacy codebase.

  • Input per task: 1,500 words (repo + instructions)
  • Output per task: 3,000 words (code + explanation)
  • Tasks: 20

Cost:

  • Input: 0.039M × $15 = $0.59
  • Output: 0.078M × $75 = $5.85
  • Total: $6.44

Batch mode would cut that to ~$3.20 total.

Example 3 — Research Summaries (Opus 4)

If you need concise, cited reports from multiple research papers.

  • Input: 4,000 words (papers + instructions)
  • Output: 8,000 words (summary + citations)
  • Runs: 12

Cost:

  • Input: 0.0624M × $15 = $0.94
  • Output: 0.1248M × $75 = $9.36
  • Total: $10.30

Claude 4 vs Other LLMs

Feature / Model Opus 4 Sonnet 4 GPT-4.1 GPT-4o Gemini 2.5 Pro
Context Window 200K 200K 128K 128K 1M (batch)
Input / Output $ $15 / $75 $3 / $15 $10 / $30 $2.5 / $10 $2.5 / $15
Coding Score (SWE) 72.5% 72.7% 69.1% 33.2% 40%
Best For Complex agents, precision code Balanced cost/performance Reasoning Speed, multimodal Google data integration

When to Choose Which Model

Claude 4 model selection guide comparing Opus 4 and Sonnet 4, showing key use cases, performance benefits, and when to skip for cheaper models like Claude Haiku or GPT-4o mini.

Go with Opus 4 if you…

  • Need multi-hour focus on a task
  • Are building AI agents that run workflows end-to-end
  • Care about highest possible code accuracy

Go with Sonnet 4 if you…

  • Want great performance but lower costs
  • Need high-volume responses without breaking the bank
  • Do lots of coding, Q&A, or summarizing where speed matters

Skip them if you…

  • Just need bulk text → use Claude Haiku or GPT-4o mini
  • Need instant multimodal audio/video → use GPT-4o

Five Proven Tricks to Keep Your Claude 4 Bill Low

I’ve tested this in real projects and found five proven strategies:

  1. Cache your system prompt — biggest savings if you reuse the same setup.
  2. Batch jobs — run big, non-urgent tasks in bulk at ~50% lower cost.
  3. Cap output length — prevent Claude from generating unnecessary text.
  4. Extended thinking only when needed — don’t pay for deep reasoning on simple queries.
  5. Use a cheaper model to pre-filter — send only the most important requests to Claude 4.

These together can cut your bill by 40–70% without hurting results.

Final Thoughts

I’ve run Opus 4 on a 7-hour autonomous coding session — it never lost track.
I’ve run Sonnet 4 on thousands of daily support chats — the cost stayed low.

If accuracy is life-or-death for your task, choose Opus 4. If you want smart, scalable AI at a lower price, choose Sonnet 4.

Who Benefits Most from Our Claude 4 Pricing Calculator?

  • Developers & MLOps Engineers – budget coding agents before provisioning GPUs.
  • E-commerce Growth Teams – forecast AI chatbot for customer support costs per order or per visitor session.
  • Product Managers – compare Claude 4 against GPT-4.1 or o3 in one click, no spreadsheet wrangling.
  • Finance & Procurement – audit every API-call assumption with a shareable permalink.
  • Agencies & Consultancies – quote fixed-fee AI projects with confidence instead of padding for “token creep.”

More Free Calculators from LiveChatAI

More Free Calculators from LiveChatAI

All benchmarks and pricing pulled from Anthropic’s “Introducing Claude 4” announcement plus publicly available model cards from OpenAI and Google.

Frequently asked questions

1. What makes Claude 4 worth the price compared to cheaper models?
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Claude 4 isn’t just about generating text — it’s about getting things right:
- Top-tier coding accuracy (Opus 4 scored 72.5% on SWE-bench Verified).
- Massive context capacity (200K tokens for huge inputs).
- Long-term focus for multi-hour AI agent tasks.
- Tool use & extended reasoning for complex workflows.
For high-stakes work, Claude 4 often saves money in the long run by avoiding costly mistakes.
2. How does Claude 4’s pricing work for hybrid (tool + model) workflows?
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If you’re building an AI agent that uses Claude plus external APIs (search, databases, or other models), remember:
- You’ll pay Claude’s token costs plus any costs for the other services.
- Tool calls might add extra input/output tokens because the results are fed back into Claude.
Budget for both, and test workflows end-to-end to avoid surprises.
3. What’s the ROI of upgrading from Sonnet 4 to Opus 4?
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From my experience, upgrading to Opus 4 makes sense when:The accuracy boost means fewer human review hours (saving payroll costs).
- The longer sustained reasoning lets you automate multi-step tasks that Sonnet might need multiple calls to complete.
- You’re working in regulated industries where mistakes carry legal or compliance risks.
If you don’t see a measurable business impact from those factors, Sonnet 4 is usually the smarter default.
4. Can I simulate multiple models at once—like Claude Opus 4 vs. GPT-4.1?
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Yes. Every result includes a side-by-side comparison of Claude Opus 4, Claude Sonnet 4, GPT-4.1, OpenAI o3, and Gemini 2.5 Pro. You’ll instantly see which model gives you the best value for your workload and which trade-offs you’re making (cost, latency, accuracy, etc.).