AI/ML API (Paid) vs HandyAI (Freemium), scored side by side on traffic, features, pricing, and audience so you can pick the right fit.
One API for 600+ AI models
AI/ML API provides a fast gateway to a wide range of AI models for various applications.
The AI dev tools you keep Googling for.
HandyAI is a growing library of single-purpose, free tools for people building with large language models.
AI/ML API leads 4 of 6 rounds
AI/ML API leads on monthly traffic, traffic growth and domain rating. HandyAI is stronger on integrations and pricing value.
The details
AI/ML API
Worldwide, desktop only
HandyAI
Top regions
AI/ML API
HandyAI
No regional data available.
What is AI/ML API?
AI/ML API is an AI DevTools platform that provides a fast gateway to over 600 AI models for various applications.
Who is AI/ML API for?
AI/ML API is designed for developers and businesses looking to integrate AI capabilities into their applications, particularly those interested in chat, reasoning, image, video, audio, voice, and search functionalities.
What can I do with AI/ML API?
With AI/ML API, you can obtain an API key for quick integration, access a wide range of AI models, utilize the AI Playground for testing, and benefit from infinite scalability for your applications.
How much does AI/ML API cost?
AI/ML API publishes a custom / contact-sales pricing model — get a quote on their site.
How is AI/ML API different from alternatives?
AI/ML API stands out by offering access to over 600 AI models with simple integration and infinite scalability, making it suitable for a wide range of AI applications.
How is the token count calculated?
For OpenAI models we run the official BPE tokenizer (`cl100k_base` for GPT-3.5/4, `o200k_base` for GPT-4o) via js-tiktoken — same exact algorithm OpenAI uses. For Claude we use Anthropic's published Claude 2 tokenizer, which matches Claude 3+ within ~5% for English text. For Gemini we approximate at ~4 chars/token because no public Gemini tokenizer exists.
Does my text leave the browser?
No. All tokenization is client-side. Nothing is sent to any server — not ours, not OpenAI's, not Anthropic's. Open your network tab and verify if you like.
Why are input and output prices different?
Providers charge more for tokens the model _generates_ than for tokens you _supply_. Output tokens are computationally more expensive because the model decodes them autoregressively. The toggle above lets you project either side of the cost.
How much does 1M tokens cost in May 2026?
Roughly: **Claude 3.5 Sonnet** is $3 in / $15 out per 1M tokens. **GPT-4o** is $2.50 / $10. **Claude Haiku** is $0.25 / $1.25. **GPT-4o-mini** is $0.15 / $0.60. **Gemini 1.5 Flash** is $0.075 / $0.30. The cheap models are 20-100x cheaper than the flagship models — a big lever for high-volume apps.
How accurate are these cost projections?
Exact for a known workload — the math is straightforward: (input × input rate) + (output × output rate), with the cached fraction billed at the model's cached-input rate. Pricing comes from each provider's published rate card. The variable is how well your typed numbers match your actual workload. If you don't know your token sizes, the [Token Counter](https://handyai.tools/tools/token-counter/) helps you calibrate against a real sample.
Stronger on monthly traffic, traffic growth and domain rating.
Stronger on integrations and pricing value.
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