Conclusion

Let’s get straight to the point: “free” means there’s no price tag, but it’s not actually free.

What’s happening in the AI industry can be summed up in one phrase: “a race to dump computational resources.”

OpenAI, Google, Anthropic—major players are competing to distribute free credits to startups. Google Cloud is offering up to $350,000 in credits for AI startups, while Microsoft Azure’s Founders Hub provides up to $150,000. OpenAI is also running a $5 million API credit program for startups.

It’s fine to see this and think, “Wow, I can use it for free.” But I want to ask one question.

Why are they going to such lengths to offer it for ‘free’?

The answer is simple: they are buying your data and your dependency.

—

The Structure of Free Credits—The ‘First Drink is Free’ Business Model

This structure is actually not new. When AWS started its cloud services in 2006, it attracted startups with free tiers, nurturing them into customers worth millions annually. The same phenomenon is now occurring in the world of AI APIs.

Let’s break down what happens specifically.

Phase 1: Free Period (0-6 months)

• Develop using free credits.
• Optimize prompt design, fine-tuning, and RAG construction for that provider’s API.
• Internal workflows are built around that API.

Phase 2: After Credit Exhaustion (6-12 months)

• The free tier expires, switching to pay-as-you-go.
• For GPT-4o, it costs $2.50 per million tokens for input and $10.00 for output.
• For Claude Sonnet 4, it’s $3 per million tokens for input and $15 for output.
• Monthly API costs suddenly spike to between $500 and $3,000.

Phase 3: Lock-in Complete (12 months onward)

• Attempting to switch to another provider requires redesigning prompts, rebuilding RAG, and retesting.
• Migration costs range from $5,000 to $20,000, which can be fatal for small companies.
• As a result, a state of “high cost but unable to change” is achieved.

This is the true nature of “free.” Zero initial costs, maximum migration costs. It’s similar to credit card annual fee waivers, but the depth of lock-in is vastly greater.

—

Breaking Down the $6 ‘Unlimited API’

On the other hand, there has been recent buzz about API services claiming “unlimited” access for a few dollars a month. ChatGPT Plus costs $20 per month, but some third-party players are offering “unlimited access” for $5 to $10 per month.

Is this really unlimited? Upon actual verification, almost without exception, the following constraints exist.

If you could truly use GPT-4o class unlimited for $6 a month, it contradicts OpenAI’s own pay-as-you-go model (which can often amount to several thousand dollars a month). There are always hidden costs associated with things that are too cheap.

For small and medium-sized enterprises, consider the following:

• If it’s just for summarizing internal meeting notes, ChatGPT Plus at $20 a month is sufficient.
• If you’re integrating it into a customer support chatbot, you should estimate monthly costs using a pay-as-you-go API.
• If you’re using around 100,000 tokens a month, GPT-4o-mini would cost a few hundred yen per month. There’s no need to jump at “unlimited.”

—

The Price Disruption of Claude Sonnet 5—Is It Really Cheap?

In 2025, Anthropic’s Claude Sonnet 4 (and its successors) gained attention for its performance-to-cost ratio. Notably, Claude Sonnet 4 costs $3 per million tokens for input and $15 for output, which is nearly on par with GPT-4o.

However, what’s noteworthy is the cost per performance. In some benchmarks, Claude Sonnet 4 demonstrates superior coding performance compared to GPT-4o while being offered at a similar price point. In other words, it can be effectively cheaper for the same tasks.

What’s crucial for small and medium-sized enterprises is not “which model is the cheapest,” but rather “how much can I get the performance I need for my business?”

Let’s consider an example. A local manufacturing company (30 employees) wants to use AI for automatic daily report summaries and anomaly detection reports.

• GPT-4o-mini: Approximately $8 per month (assuming about 500,000 tokens per month)
• GPT-4o: Approximately $35 per month
• Claude Sonnet 4: Approximately $40 per month
• Using free credits: $0 (but $40 per month after 6 months + risk of being unable to migrate)

For this scale of use, GPT-4o-mini is sufficient. At $8 per month, there’s no need to jump at ‘free.’

—

Three Actions Small and Medium-sized Enterprises Should Take

Let’s move beyond abstract discussions and outline specific actions to take.

1. Design with Multi-Provider in Mind

Don’t create systems that are exclusively for OpenAI or Anthropic from the start. By using LiteLLM, OpenRouter, or OpenAI-compatible API formats, the cost of switching backend models can dramatically decrease.

A migration cost of $20,000 can be reduced to $500 depending on the design. This difference can be a matter of life and death for small businesses.

2. Calculate Monthly Token Usage in Advance

Before being swayed by “unlimited” or “free,” estimate your company’s monthly token consumption. Many small and medium-sized enterprises find their usage falls below 1 million tokens per month. For GPT-4o-mini, that would be around $1.50 to $6 per month.

Is it necessary to be locked in by being lured by something that costs a few hundred yen per month?

3. Decide Where to Store Your Data

Many free credits assume that data will be processed on the provider’s cloud. If you’re sending customer data or internal confidential information there, check the contract to confirm “who owns that data” and “will the data be deleted upon cancellation?”

It’s too late to start using it and then ask, “Can I have my data back?” without confirming.

—

In an Era Where the Meaning of ‘Cheap’ Has Changed, What Will You Choose?

The inference costs of AI have decreased by about 100 times in the past two years. What used to cost $60 per million tokens for GPT-4 in 2023 is now $0.15 for GPT-4o-mini in 2024. That’s 400 times cheaper.

What this trend signifies is that the “cost of using AI” is no longer a competitive advantage. Anyone can use it cheaply. The differentiation lies in “what you use it for” and “how you integrate it into your operations.”

Whether to jump at free credits or to pay a few hundred yen a month to maintain freedom—this choice will determine whether you incur a migration cost of $20,000 a year from now or if you can avoid it altogether.

For local small and medium-sized enterprises, $20,000 is equivalent to a single investment in new equipment. Will you use it to break free from lock-in or invest it in your next business?

Read the price that isn’t labeled as ‘free.’