OpenAI vs Anthropic API pricing: which is actually cheaper?

If you are choosing between OpenAI and Anthropic on price, the honest answer to "which is cheaper" is: it depends on the tier you need, how your text tokenizes, and how much you cache — and at least once this year the cheaper option flips. This is a claim-and-evidence walk through OpenAI vs Anthropic API pricing at every tier, with the numbers that actually decide your bill rather than the ones on the pricing page.

Two rules before the table. First, price is quoted per million tokens, but you pay per token your text actually becomes — and the two providers tokenize the same text differently. Second, list prices move; the figures below are dated, and a couple of them expire on a date we will name.

The sticker prices, tier by tier

Here are the current list prices, tier-matched — flagship against flagship, workhorse against workhorse, budget against budget, plus OpenAI's dedicated reasoning model. Cached input is the discounted rate for reading a previously cached prompt prefix.

"Intro" marks Claude Sonnet 5's introductory rate: it lists $2 / $10 per million tokens through 2026-08-31, then rises to $3 / $15, with its cache and batch rates scaling in proportion. GPT-5.4 mini's context window is not published in the source dataset, shown as "—".

Read the flagship row carefully

On paper the flagship tier is a near-tie that tilts to Anthropic. For a representative request of 10K input and 1K output tokens, Claude Opus 5 costs $0.075 and GPT-5.6 Sol costs $0.080 — about 6% apart. If price were the whole story you would stop here and pick Opus 5. Price is not the whole story.

The tokenizer trap: per-token price is not cost per task

A price of "$5 per million tokens" only tells you your bill if you know how many tokens your text becomes, and that depends on the tokenizer. Anthropic's newest-generation models — Opus 5 and the premium Fable 5 — use a tokenizer that produces roughly 30% more tokens for the same English text than the previous generation. Price the same actual prompt on both sides and the flagship comparison inverts: the request that is 10K input / 1K output on GPT-5.6 Sol is closer to 13K / 1.3K on Opus 5, which moves Opus 5 from $0.075 to about $0.098 — now roughly 22% more expensive than GPT-5.6 Sol for identical text. The lesson is general: compare cost per task on your own prompts, not headline price per million tokens.

This cuts both ways. Anthropic's mid and budget models — Sonnet 5 and Haiku 4.5 — do not carry the newer-tokenizer note, so their sticker prices are directly comparable to OpenAI's. Always check whether a per-token price is even denominated in the same tokens before you trust a comparison.

The mid-tier intro-price cliff

The workhorse tier is where most production traffic lives, and today it favors Anthropic — with an asterisk. Claude Sonnet 5 on its introductory price ($2 / $10) runs the 10K/1K request at $0.030 against GPT-5.4's $0.040 — 25% cheaper, and text-for-text, because Sonnet 5 uses the standard tokenizer. But the intro price expires 2026-08-31. After that Sonnet 5 lists $3 / $15, taking the same request to $0.045 — now about 12% more than GPT-5.4. If you are latching a budget to Sonnet 5's mid-tier price, put a reminder on that date.

The budget tier goes to OpenAI

At the small-and-fast end, OpenAI is cheaper: GPT-5.4 mini runs the 10K/1K request at $0.012 versus Claude Haiku 4.5's $0.015, about 20% less. And OpenAI's line extends well below mini — GPT-5.6 Luna and GPT-5.4 nano list at $0.20 input, and legacy GPT-5 nano at $0.05 — territory Anthropic's public API does not price against today. If your workload is high-volume classification, extraction, or routing, that gap compounds; the cheapest-LLM guide linked below ranks the whole budget field.

Cache and batch: where the real savings hide

Both providers discount reading a cached prompt prefix by 90% on their GA flagship and workhorse models — Opus 5 and GPT-5.6 Sol both drop cached input from $5.00 to $0.50; Sonnet 5 goes $2.00 to $0.20. Two differences decide which cache is cheaper for you. First, Anthropic charges a cache-write premium: populating the cache costs about 1.25× the base input rate (Opus 5 writes at $6.25 against $5.00 input), so the cache pays off only once a cached prefix is reused enough to amortize that write — whereas OpenAI's cache is automatic, with no separate write charge in its published table. Second, OpenAI's dedicated reasoning models (o3, o4-mini) discount cached reads by 75%, not 90%. For asynchronous work, both offer a Batch API at 50% off. If you run a long, stable system prompt across many calls, model the cache explicitly — it moves the answer more than the sticker price does.

Which should you pick

There is no single winner; there is a winner per workload:

• ◦High-volume budget work (classification, extraction, routing): OpenAI. GPT-5.4 mini undercuts Haiku 4.5, and the nano tier goes lower still.
• ◦Mid-tier production traffic, today: Claude Sonnet 5 on its intro price — cheaper text-for-text than GPT-5.4. Revisit on 2026-08-31, when the intro ends and the tier flips to GPT-5.4.
• ◦Flagship quality: a near-tie on sticker that GPT-5.6 Sol wins once you account for Anthropic's ~30% higher tokenization on Opus 5 — unless you lean on a heavily reused cached prompt, where Anthropic's 90% read discount closes the gap.
• ◦Either way: decide on cost per task for your real input:output ratio, cache-hit rate, and tokenizer — not on price per million tokens.

Is OpenAI or Anthropic cheaper?

It depends on the tier. For budget, high-volume work OpenAI is cheaper — GPT-5.4 mini at $0.75 / $4.50 undercuts Claude Haiku 4.5 at $1.00 / $5.00. For mid-tier work Claude Sonnet 5 is cheaper on its introductory price until 2026-08-31, then GPT-5.4 takes the lead. At the flagship tier the two are within about 6% on sticker, and GPT-5.6 Sol pulls ahead once you adjust for Anthropic's higher tokenization.

How much does prompt caching save with each provider?

Both cut the price of reading a cached prompt prefix by 90% on their GA flagship and workhorse models. The difference is on the write side: Anthropic charges roughly a 25% premium to write into the cache, so reuse has to be high enough to earn it back, while OpenAI caches automatically with no separate write fee. OpenAI's o-series reasoning models discount cached reads by 75% rather than 90%.

Why don't the sticker prices predict my bill?

Because you are billed per token, and the same text becomes a different number of tokens on each provider's tokenizer — Anthropic's newest models run about 30% higher than the prior generation. Your input:output ratio and cache-hit rate matter just as much. Two models with identical per-million prices can produce very different monthly bills, so price your own token mix.

Do these prices change often?

Yes. Claude Sonnet 5's introductory price expires 2026-08-31, and OpenAI cut GPT-5.6 Luna sharply in late July 2026. Treat any published price as dated — the figures here are list prices as of 2026-08-03 — and re-verify against the provider's pricing page before you commit a budget.