AI API Pricing Guide: Every Provider Compared

Example 1: Chatbot Application (10,000 conversations/month)

Assuming each conversation averages 2,000 input tokens and 1,000 output tokens:

The takeaway: there is roughly a 100x cost difference between the most expensive and cheapest options for the same workload. Choosing the right model matters enormously. *Gemini 3.8 Flash is at an introductory rate through December 31, 2026; Google has published that both rates double on January 1, 2027. Gemini 4 Argon is shown at its December 1 price of $4/$20 (it is $2/$10 until then). **Claude Haiku 5.5 bills $0.10/$0.50 for prompts up to 100K tokens; its newer tokenizer produces roughly 30% more tokens for the same text, so its real bill runs somewhat higher than this like-for-like estimate.

Example 2: Document Summarization (1,000 documents/month)

Assuming each document is 10,000 input tokens and the summary is 500 output tokens:

Example 3: Code Generation (500 requests/day)

Assuming 1,500 input tokens (prompt + context) and 2,000 output tokens (generated code) per request:

1. Use the smallest model that works

This is the single most impactful optimization. For many tasks, GPT-6 Luna, Claude Haiku 5.5, or Gemini 3.8 Flash produces results that are nearly as good as frontier models at a fraction of the cost. Test your use case with cheaper models first and only upgrade if quality is genuinely insufficient. A model that is 10x cheaper and 95% as good is almost always the right choice.

2. Implement caching

If users ask similar questions, cache the responses. Both Anthropic and OpenAI offer prompt caching that cuts the cost of repeated prefixes by 90% or more (cache reads on Claude Fable 5.1 cost just 2.5% of the base input price, and on Claude Opus 5.5 they cost 5%, or $0.20 per million tokens). Even simple application-level caching (storing responses for identical inputs) can save significant money.

3. Optimize your prompts

Shorter prompts cost less. Remove unnecessary instructions, examples, and context. Use system prompts efficiently. If you are including few-shot examples, test whether you really need all of them. Often 1-2 examples work nearly as well as 5-6.

4. Set max token limits

Always set a max_tokens parameter to prevent unexpectedly long (and expensive) responses. For a summarization task, you probably do not need more than 500 output tokens. For code generation, 2,000 is usually plenty.

5. Use model routing

Route different requests to different models based on complexity. Simple questions go to a cheap model; complex ones go to a frontier model. You can implement this with a classifier (which itself can be a cheap model) or with simple heuristics based on input length or keywords.

6. Batch your requests

Both OpenAI and Anthropic offer batch APIs with 50% discounts. If your use case does not require real-time responses (e.g., processing a backlog of documents), batching can cut your costs in half.

7. Consider open source models

For high-volume applications, self-hosting an open source model like DeepSeek V4.1 Flash or Qwen3.8-27B can be dramatically cheaper than API calls. The upfront infrastructure cost is higher, but per-request costs approach zero. See our open source LLM guide for details.

How much does the OpenAI API cost?

OpenAI API pricing varies by model. GPT-6 Astra, the current flagship, costs $10 per 1M input tokens and $50 per 1M output tokens. GPT-6 Sol ($2/$10) and GPT-6 Luna ($0.10/$0.50) launched on September 22, 2026 at permanent rates, with prompts above 272K input tokens billed at a higher tier. The GPT-5.6 family runs from Sol at a promotional $4/$20 to Terra at $2/$12 and Luna at $0.20/$1.20, and GPT-6.1 Sol arrived on September 29 at $2/$10. Older models are on the way out: OpenAI's October 14 notice shuts down o1, o1-pro, and o3-mini on October 23, 2026 and removes the GPT-4o, GPT-4o-mini, GPT-4.1, and GPT-4.1-mini snapshots on January 14, 2027.

What is the cheapest AI API?

In our pricing data, NVIDIA's Nemotron 3.5 Lightning is among the cheapest at $0.08 per 1M input tokens, with poolside's Laguna S 2.1, OpenAI's GPT-6 Luna, and Anthropic's Claude Haiku 5.5 (for prompts up to 100K tokens) all at $0.10. Gemini 2.0 Flash, long a budget default at $0.10, was shut down on June 1, 2026. Open-weight models like DeepSeek V4.1 Flash and Qwen3.8-27B are free to self-host.

How are AI API tokens counted?

Roughly, 1 token equals about 4 characters or 0.75 words in English. A 1,000-word document is approximately 1,333 tokens. Most APIs charge separately for input (prompt) and output (completion) tokens.

Which AI API is best for production?

For reliability and quality, Anthropic (Claude Opus 5.5 and Sonnet 5.5) and OpenAI (GPT-6 Astra, GPT-6.1 Sol, and GPT-6 Sol) are the most popular choices, with Google's Gemini 4 Argon, generally available since October 13, now in the same conversation. For cost-sensitive applications, Gemini 3.8 Flash, GPT-6 Luna, Claude Haiku 5.5, or self-hosted open-weight models offer the best value.