OpenAI Flex vs Fast vs Standard Cost Calculator
Price one workload on every OpenAI processing tier. Pick a GPT-6 model, enter monthly input, cached input, and output tokens. Each tier = uncached input × input rate + cached × cached rate + output × output rate from that tier’s official column. Flex ≈ half of Standard, Fast ≈ 2×, Ultrafast (Astra/Sol only) ≈ 6×. Estimates only; official OpenAI pricing prevails.
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Standard
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Flex
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Fast (formerly Priority)
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Ultrafast
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Estimates only; official vendor pricing prevails (2026-10-30). Cost per tier = uncached input × input rate + cached input × cached rate + output × output rate, using that tier’s published column. Flex shares the Batch column on the official table; for async jobs see the Batch calculator.Official pricing: OpenAI
OpenAI Batch API Savings Calculator · OpenAI Token Cost Calculator · LLM Prompt Caching Cost Calculator · LLM API Cost Calculator
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- LLM API Cost Calculator Generic token cost from any $/1M rates.
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How it works
- How is each tier priced?
- Each tier uses its own official column: uncached input × input rate + cached input × cached rate + output × output rate. Example: GPT-6.1 Sol, 10M input, 2M output → Standard $40, Flex $20 (−50%), Fast $80 (+100%), Ultrafast $240 (+500%).
- What is Flex processing?
- Flex trades latency and availability for a lower price. On the official table Flex shares the Batch column, roughly half of Standard (GPT-6.1 Sol $1 / $5 vs $2 / $10 per 1M).
- What is Fast mode?
- Fast mode (renamed from Priority processing on 2026-07-30) gives faster, more reliable processing at about 2× Standard. Ultrafast is listed only for GPT-6 Astra and GPT-6.1 Sol at about 6× Standard.
- Should I use Batch instead of Flex?
- Batch is for asynchronous jobs with a completion window, at the same ~50% rates. Use the OpenAI Batch API savings calculator for that comparison; this page covers synchronous tiers.
- Are results billing-grade?
- No. Regional/data-residency endpoints add a 10% uplift on newer models. Estimates only; official OpenAI pricing prevails.