Table of Contents
Should You Speak English to AI? A Practical Guide to Cost Reduction and Performance Enhancement
Speaking Japanese to AI Might Be "Losing Money"
Super Practical Techniques: How English Can Dramatically Reduce Costs and Unlock AI Performance
【Important: Please Read First】
The information in this article is based on research as of September 24, 2025. Generative AI technology, pricing structures, and tokenization specifications may change without notice due to updates from various companies. The prices and figures mentioned are purely illustrative examples.
When using actual services, please always verify the latest accurate information on official websites and use it at your own judgment and responsibility.
Introduction: What's the Real Cause of Your AI Cost Problem?
Everyone has their own relationship with generative AI. For those who use services like ChatGPT for daily conversations and brainstorming, the main concern might be "hitting the free plan limits too quickly."
However, for developers and power users who leverage AI agents (like Cursor) for development or integrate APIs into their services, the real headache is the "pay-per-use" costs snowballing out of control.
💸 Why Traditional Solutions No Longer Work
Previously, there was an approach where you could somewhat stabilize costs by using specific models like Codex. However, recently even these models have strict usage limits and time restrictions (rate limits), and it's not uncommon to see merciless notifications like "You can't use this for another X hours" at crucial moments.
🎯 The Real Challenge We Must Face Now
So there's one challenge we really need to confront:
How to use top-performance "professional-grade" models like GPT-5 and Gemini 2.5 Pro smartly, efficiently, and sustainably.
In this article, I propose the simplest yet most powerful solution to this challenge:
💡 Solution: "Switch your primary AI conversations from Japanese to English"
🔰 Middle School English Is Enough
And don't worry. The English I'm talking about here is definitely not fluent business English.
- Simple vocabulary and grammar from middle school level is sufficient
- AI can intelligently understand even if some Japanese is mixed in
- You can start casually without aiming for perfection
This article provides a thorough explanation based on the latest data and facts about specific methods and why this dramatically reduces costs, improves AI response speed and quality, and even enhances your English skills.
Part 1: The Inconvenient Truth. Why Japanese Is a "Fuel-Inefficient Language" for AI
AI doesn't understand language like humans do. It breaks down text into units called "Tokens" and processes their relationships mathematically. And this "Token" is the fundamental reason why Japanese users are at a disadvantage cost-wise.
📊 Fact: Japanese Consumes More Tokens Than English
Due to language characteristics, the same amount of information creates significant differences in token consumption.
- Words are separated by spaces, so they're efficiently tokenized in "word" or "sub-word" units
- Example:
"AI is powerful."→ About 4 tokens
For English
- There are no word boundaries, so text tends to be tokenized into character or short morpheme units
- Example:
「AIはパワフルです。」→ About 10 tokens
For Japanese
⚠️ Important Fact
To convey the same information, Japanese sends 1.5 to 3+ times the "data volume" to AI compared to English. This ratio varies depending on the content and AI model.
💰 Data: The "Output Token" Trap That Dominates Costs
Most AI API pricing is set up as follows:
- Input tokens: Instructions humans send to AI
- Output tokens: Responses AI generates and returns
And "output" where AI generates text is generally priced higher than "input" where humans give instructions.
| Model (Example prices as of Sep 24, 2025) | Input Rate (per 1M tokens) | Output Rate (per 1M tokens) |
|---|---|---|
| GPT-5 | $8.00 | $24.00 (3x) |
| Claude Sonnet 4 | $4.00 | $20.00 (5x) |
| Gemini 2.5 Pro | $5.00 | $15.00 (3x) |
⚠️ Note: The above prices are examples for illustration. Please always check the latest pricing on official websites.
💸 Actual Cost Calculation: Requesting Report Creation
Let's compare the costs when requesting the same content report.
- Total tokens (estimated): About 12,000 tokens
- GPT-5 cost (estimated): About $0.29
Japanese instruction・Japanese output
- Total tokens (estimated): About 4,000 tokens
- GPT-5 cost (estimated): About $0.09
English instruction・English output
📊 Analysis Result
As this calculation shows, just the difference in language can create a 3x+ difference in costs.
Part 2: Four Benefits You Can Expect from Switching to English
Cost reduction is just the beginning. Making English your working language with AI can further improve your productivity.
💰 Benefit ①: Improved Cost Performance
As mentioned above, you can expect dramatically improved cost efficiency compared to Japanese for API fees and paid plan usage limits.
🎯 Benefit ②: Improved Answer "Quality" and "Freshness"
- Major AI models worldwide are said to be composed primarily of English text in their training data
- Especially for specialized fields, latest technology, and niche topics, asking in English is advantageous
Impact of Training Data Language Ratio
- Deeper, more accurate responses based on the latest information are likely to be returned
- The abundance of technical documents and documentation is reflected
Expected Effects
⚡ Benefit ③: Improved AI Response Speed
- Generally, the fewer tokens AI generates, the shorter the processing time tends to be
- English output requires fewer tokens than Japanese, so AI responses may become faster
Impact on Processing Speed
⚠️ Note: Speed is also affected by other factors like server congestion
🏋️ Benefit ④: Becomes a Practical "English Gym"
- Do you feel like "my English skills are declining..."?
- AI can be your English "practice partner" 24/7/365
Continuous English Learning Opportunities
- Since AI can understand your intent even with some grammar mistakes, you can work without fear of imperfection
- You can conduct practical reading (reading AI responses) and writing (giving instructions) training in your daily work
Learning Effects
Part 3: Start Today! AI English Utilization・Practical Steps
You don't need to switch everything to English immediately. You can start with simple steps.
🔰 Suggestion 1: Don't Overthink It! Middle School English Is Enough, Japanese Mixed In Is OK
- AI has very high contextual understanding ability, so perfect sentences aren't necessary
- Even just lining up keywords, AI can understand your intent
- If you can't think of difficult words, using just Japanese for those parts is fine
Leverage AI's High Contextual Understanding
React component, カードデザイン, sample code pleasesummary, this article, 3 pointsfunction, calculates 消費税, input is price
Good Examples: Mixed Language Instructions
🛠️ Suggestion 2: Use Translation Tools as Your "Crutch"
- Always keep DeepL or Google Translate by your side
- First translate instructions you think in Japanese to English using translation tools, then send to AI
- This alone can reduce input costs
Efficient Input Cost Reduction Method
🚀 Suggestion 3: Try the Ultimate Workflow "Generate in English → Human Translation"
3-Step Efficient Workflow
- Give instructions (prompts) in simple English
- Receive AI responses in English too, of course
- Copy the entire English response and run it through translation tools as needed
💡 This procedure is, in many cases, one of the most cost-, speed-, and quality-balanced AI utilization techniques.
👨🏫 Suggestion 4: Make AI Your "English Teacher"
- Don't worry if you're not confident in your English
- Have AI correct it for you
- Try adding the following "magic spell" at the end of your prompts
Utilize English Correction Features
Correction Request Template
First, please correct and improve my English prompt for clarity and effectiveness. Then, answer the improved prompt.
This way, AI will correct your English and teach you better ways to give instructions.
Conclusion: Tomorrow's Standard, In Your Hands Today
Switching AI interactions from Japanese to English isn't just a cost-cutting technique.
🌟 The Essence of This Approach
It's an extremely strategic self-investment that maximizes AI tool performance, provides direct access to global information, and simultaneously sharpens your English skills.
🚀 Action Starting Today
You don't need to aim for perfect English.
Starting today, why not incorporate just a little "casual English" into your AI conversations?
That small step might become the trigger that dramatically changes your productivity and future.
I hope this article helps make your AI utilization more efficient and practical. 🤖✨

NEW NOVEL 2026/08/01
Clouded Glass
Polishing is not about force.
Volume two of The World Became Slightly Farther Away.Five stories that can also be read as a starting point.
View on Amazon
Jijoden.com
Your life is worth writing.
There is a truer self you can tell only to AI.Gather fragments of memory into a single story.
Take a LookRelated Articles
The Day AI Got Borders: Will Intelligence Be Export-Controlled?
A long-form essay on the suspension of Claude Fable 5 and Claude Mythos 5, model weights, export controls, cyber defense, technological sovereignty, and who should govern dangerous knowledge.
Complete Guide to OpenAI Agent Builder: From Generative AI and AI Agents to the Latest Platform
A comprehensive guide to OpenAI's Agent Builder announced in October 2025, covering the fundamentals of generative AI and AI agents, no-code agent development, and comparisons with competing products.
What is RAG (Retrieval-Augmented Generation)? Complete Guide to Generative AI, AI Agents, and MCP
A beginner-friendly guide to RAG (Retrieval-Augmented Generation), explaining its differences and relationships with Generative AI, AI Agents, and MCP, including how ChatGPT's web search relates to RAG.
What I Learned from Trading FX with LLMs
A detailed log of building an AI-powered automated FX trading system and running it live for a month, revealing what LLMs are bad at and where they actually shine.
Deconstructing Gemini Spark: 24/7 Always-On AI Agent Architecture
The paradigm shift of 'Autonomous Always-On AI' brought by Gemini Spark. We explore the Long-Horizon execution engine orchestrating Google Workspace and provide a direct comparison with Claude Cowork and Anti-Gravity.