Claude Haiku 5.5 or GPT-6 Luna? Price, Performance and Which Saves Your Business More

On list price they are identical: $0.10 per million tokens going into the model and $0.50 per million tokens coming out. Which one saves your business more depends on the work. Claude Haiku 5.5, released by Anthropic on 7 October 2026, is stronger at computer use and practical tasks, but it uses more tokens per task, and its price rises 5x once a request passes 100,000 tokens. OpenAI's GPT-6 Luna is more frugal with tokens, cheaper on long requests, and knows more general facts. The rule: test both on your own data before you decide.

What are these two models, and why do businesses care?

Both belong to the small, fast class of models. These are not the models that write you a complex business plan; they work quietly behind systems thousands of times a day, answering customer questions, sorting requests, summarizing conversations and pulling data out of invoices. In that kind of work the same request repeats millions of times, so a one-cent difference in price becomes a real difference in the monthly bill.

Anthropic's announcement calls Haiku 5.5 the cheapest, fastest and most capable small model it has released, and says it costs around 75% less to run on average than Haiku 4.5. OpenAI's official page describes Luna as its most efficient model for focused, high-volume tasks. To see where Luna sits among its siblings, read GPT-6 Astra vs Sol vs Luna.

Price comparison: equal on paper

Prices are in US dollars per million tokens, from both companies' official pages. A token is roughly part of a word, and a million tokens is about 555,000 words according to Anthropic's documentation. In brackets is the riyal equivalent at the official rate of 3.75 SAR to the dollar.

The difference that matters is long requests. If your business sends the model long documents, such as contracts or reports between 100,000 and 272,000 tokens, Haiku 5.5 costs 5 times its base price while Luna stays at its normal rate. Anthropic says about 90% of requests to its previous Haiku were under 100,000 tokens, so most everyday use is unaffected.

Performance comparison: which is stronger?

Anthropic published a comparison of the two models, and the independent site Artificial Analysis published its own results. These are the main figures; note that the maker's numbers are measured by the maker itself:

In plain words: Haiku 5.5 is stronger at carrying out practical tasks on a computer, and more often admits it does not know instead of inventing an answer. Luna knows more general facts. On an automation test, Haiku 5.5 scored 35% against 53 to 60% for Luna and similar models, but Artificial Analysis says the result is probably understated because of an over-refusal issue Anthropic is fixing.

Which actually saves more? List price is not everything

Price per million tokens is not enough to judge, because a model that uses more tokens per task costs you more even at the same price. This is the key difference according to Artificial Analysis: at max effort, Haiku 5.5 uses about 162,000 output tokens per task, roughly 3 times Luna's 50,000 or so. Even at similar intelligence, Haiku 5.5 used about 55,000 tokens against 50,000 for Luna.

An example from our own arithmetic: a customer service assistant handling 10,000 conversations a month, each with 2,000 input tokens and 500 output tokens, costs about $4.50 a month at list price on either model, roughly 17 riyals. If one model used twice the output tokens because of longer thinking, it would rise to about $7. Both numbers are small, but the gap grows once you reach millions of requests.

What is new for both models is that you control the effort level. Haiku 5.5 is the first Haiku-class model to support it, with medium as the default. Luna supports levels from no thinking up to maximum effort. Choose low effort for simple tasks such as classification, and raise it only when you need more accuracy.

When should you choose each?

• Choose Claude Haiku 5.5 for tasks where the model carries out steps on a computer or in a browser, for customer service that needs high speed, and where admitting uncertainty matters more than breadth of knowledge.
• Choose GPT-6 Luna for long documents between 100,000 and 272,000 tokens, for tasks that need broader general knowledge, and when lower token use per task matters to you.
• Either way, test both on a sample of your real data and measure cost per task, not per million tokens. If you handle customers' personal data, check where it is processed before sending it.

For more on the gap between token price and real task cost, read why a task can cost less when the price has not changed.

The bottom line

Claude Haiku 5.5 and GPT-6 Luna share the same list price but differ in how they consume tokens and where they are strong. Haiku is stronger at practical tasks and more honest when it does not know; Luna is more frugal with tokens and cheaper on long requests. The one that saves your business more is the one with the lowest cost per task on your own data, not the one that looks cheaper in a table.

Sources: Anthropic's Claude Haiku 5.5 announcement (7 October 2026): https://www.anthropic.com/claude-haiku-5-5 , the model's documentation on the Claude Platform, OpenAI's official GPT-6 Luna page, and Artificial Analysis's independent review of the model.