OpenAI vs Claude API Pricing: Same Workload, Real Numbers
Short answer: at the budget tier OpenAI is far cheaper (GPT-5.6 Luna is 5x below Claude Haiku 4.5 on input), at mid tier the two tie on input with Sonnet 5 $2 cheaper per 1M output tokens, and at flagship level GPT-5.6 Sol's promo undercuts Opus 5 by 20% — but only through November 21, 2026, and only below the 272K long-context threshold.
The verdict in four lines
Head-to-head pricing table
Standard first-party text rates per 1,000,000 tokens. OpenAI data verified 2026-08-23; Claude rates verified 2026-08-09 to 2026-08-16.
| Tier | OpenAI | Claude | Input verdict | Output verdict |
|---|---|---|---|---|
Flagship Hardest reasoning | GPT-5.6 Sol — $4.00 / $20.00Promo | Claude Opus 5 — $5.00 / $25.00 | OpenAI −20% (promo) | OpenAI −20% (promo) |
Mid Balanced default | GPT-5.6 Terra — $2.00 / $12.00 | Claude Sonnet 5 — $2.00 / $10.00 | Tie at $2.00 | Claude −$2.00 / 1M |
Budget High-volume tasks | GPT-5.6 Luna — $0.20 / $1.20Lowest | Claude Haiku 4.5 — $1.00 / $5.00 | OpenAI 5x cheaper | OpenAI ~4x cheaper |
Rates in USD per 1M input/output tokens. GPT-5.6 Sol's $4.00/$20.00 is promotional through at least Nov 21, 2026 (previously $5.00/$30.00). Prompts over 272K input tokens on GPT-5.6 models use higher long-context rates, not shown here. Sonnet 5's planned Sep 1, 2026 increase was cancelled. Caching, batch, tools and taxes excluded.
Identical document workload, priced monthly
Fixed profile: 60K input + 1K output tokens per request, 1,000 requests per day — 1.8B input and 30M output tokens per 30-day month. No list-price comparisons; this is the same work billed two ways.
| Model | Input cost / mo | Output cost / mo | 30-day total |
|---|---|---|---|
GPT-5.6 Sol OpenAI · flagship (promo) | $7,200.00 | $600.00 | $7,800.00 |
Claude Opus 5 Anthropic · flagship | $9,000.00 | $750.00 | $9,750.00 |
GPT-5.6 Terra OpenAI · mid | $3,600.00 | $360.00 | $3,960.00 |
Claude Sonnet 5 Anthropic · mid | $3,600.00 | $300.00 | $3,900.00 |
GPT-5.6 LunaLowest OpenAI · budget | $360.00 | $36.00 | $396.00 |
Claude Haiku 4.5 Anthropic · budget · 200K context | $1,800.00 | $150.00 | $1,950.00 |
Computed from published per-1M rates on the fixed profile above; your tokenization and caching behavior will differ. Run your own volumes in the live calculator below.
Your workload on OpenAI vs Claude
Pick a preset or enter per-request token volumes and daily requests. All six models from both providers are priced side by side; OpenAI long-context rates apply automatically above 272K input tokens.
| Model | Per request | Per day | 30-day estimate |
|---|
Where the gap actually starts to matter.
Mid tier: Terra and Sonnet 5 tie on input, so the entire difference is $2.00 per 1M output tokens. At 30M output tokens a month that is $60 — noise. At 500M output tokens a month it is $1,000 — worth a routing decision. The break-even is not a usage level; it is your output volume times $2.
Flagship: Sol's promo saves $1.00 per 1M input and $5.00 per 1M output versus Opus 5 — $1,950/month on the workload above. The break-even here is a date: November 21, 2026. If Sol returns to $5.00/$30.00, input ties and Opus 5 undercuts output by $5.00 per 1M, flipping the answer for output-heavy traffic.
Long context: the sharpest break-even is a token count. Below 272K input tokens, Terra and Sonnet 5 are near-identical. Cross 272K and OpenAI's long-context rates apply (input ×2, output ×1.5): a 400K-token request costs about $1.64 on Terra vs $0.82 on Sonnet 5 — Claude becomes roughly 50% cheaper per long request.
Same text, different tokenizers — and other traps.
Both flagships and both mid-tier models accept roughly 1M tokens (1,050,000 on GPT-5.6, 1,000,000 on Claude), so context fit rarely decides between Sol/Terra and Opus/Sonnet. The budget tier is different: Haiku 4.5 caps at 200K tokens while Luna accepts 1.05M — long transcripts and repos cannot route to the cheapest Claude.
Tokenizers differ between providers, so the same document can meter several percent differently — measure real prompts with the Token Counter before committing. Caching changes the math too (GPT-5.6 Sol cached input is $0.40 per 1M); neither provider's cache or batch discounts are modeled on this page. Max output is 128K tokens on both families except Haiku 4.5 at 64K.
OpenAI vs Claude pricing questions
Is OpenAI or Claude cheaper?
It depends on the tier. Budget: GPT-5.6 Luna ($0.20/$1.20 per 1M input/output) is 5x cheaper on input than Claude Haiku 4.5 ($1.00/$5.00). Mid tier: GPT-5.6 Terra and Claude Sonnet 5 tie on input at $2.00, but Sonnet 5 is $2.00 cheaper per 1M output tokens ($10 vs $12). Flagship: GPT-5.6 Sol's promotional rate ($4.00/$20.00, through at least Nov 21, 2026) undercuts Claude Opus 5 ($5.00/$25.00) by 20% on both input and output.
OpenAI vs Claude: which is cheaper for long documents?
Claude, in most cases. OpenAI applies long-context rates once a prompt exceeds 272K input tokens (input price doubles, output price rises 1.5x on GPT-5.6 models), while Claude keeps flat rates up to its 1M-token window. A 400K-token request costs about $1.64 on GPT-5.6 Terra at long-context rates versus $0.82 on Claude Sonnet 5. Claude Haiku 4.5 is the exception — its 200K context window cannot take long documents at all.
What is the real price difference between GPT-5.6 Terra and Claude Sonnet 5?
Only the output rate differs: $12.00 vs $10.00 per 1M tokens, a $2.00 gap. On a document-processing workload of 1.8B input and 30M output tokens per month, that gap is about $60 per month ($720 per year) in Sonnet 5's favor — the input side is identical, so the break-even question is output volume and quality, not base price.
Does the GPT-5.6 Sol promotional price change the flagship comparison?
Yes. Through at least November 21, 2026, Sol costs $4.00/$20.00 per 1M input/output tokens — 20% below Claude Opus 5 on both axes. If Sol returns to its pre-promotion $5.00/$30.00 rate, input costs tie and Opus 5 becomes $5.00 cheaper per 1M output tokens, flipping the flagship answer for output-heavy workloads.
Are token counts the same across OpenAI and Claude?
No. OpenAI and Anthropic use different tokenizers, so the same text can produce token counts that differ by several percent. Before migrating a workload, measure your real prompts with a token counter and validate with each provider's official tokenizer or usage API.
Where these numbers come from.
All rates are taken from the providers' official pricing documentation and re-verified weekly. Workload costs multiply fixed token volumes by published per-million-token rates; they do not estimate tokenization and do not apply caching or batch discounts. "Best fit" on this page is a cost result, not a quality ranking — benchmark both providers on your own prompts.
Official sources: OpenAI model docs and Anthropic pricing. Always confirm the invoice before making purchasing decisions.