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Is Claude or OpenAI prompt caching cheaper in practice?

Historical consensus 2026-08-18 Active
Runs Weekly on Tuesday at 09:00 (Europe/Berlin) Last 2026-09-01 09:17 Europe/Berlin Next 2026-09-08 09:00 Europe/Berlin

Movement at this check

Changed since last check

The answer itself held, but the models now agree more than in the recent checks (+26 pts). Refined the pricing comparison to clarify that both providers offer similar cache read discounts (~90%) and that total cost differences often stem from underlying base model prices, while maintaining the same core conclusions regarding which provider to choose for different workload patterns.

Direction shift
—
Agreement
+26 pts vs previous check

Agreement over time

64/100
2026-08-11: 64/100 · No material movement 2026-08-18: 90/100 · Refined the pricing comparison to clarify that both providers offer similar cache read discounts (~90%) and that total cost differences often stem from underlying base model prices, while maintaining the same core conclusions regarding which provider to choose for different workload patterns. 2026-08-25: 75/100 · Restated, not moved: The consensus shifted from stating OpenAI is usually cheaper in default practice to clarifying that neither is universally cheaper. It adds explicit mathematical breakdowns, details on OpenAI's tiered cache read discounts (0.1x to 0.5x) vs. Claude's write premiums/5-minute window, and broader workload nuances. 2026-09-01: 64/100 · No material movement View full chart
You are viewing a historical version. Return to current consensus
90 /100
agreement
  • 3 AI models
  • 0 contradictions
  • 21 sources
Consensus OpenAI GPT-5.4 mini
Models consulted
  • OpenAI GPT-5.6 Luna
  • Google Gemini Gemini 3.7 Flash
  • Grok Grok 4.3 · No reasoning

Consensus at this check

Short answer: usually OpenAI is cheaper in practice if you compare similar-capability models and you get decent cache hits; Claude can be cheaper in high-reuse, stable-prefix workflows, especially when its explicit caching fits your request pattern well.

Why:

  • The cache discount itself is broadly similar on current flagship-style offerings: cached reads are around 90% cheaper than normal input for both, and cache writes are typically 1.25× input for short-lived caching; Claude also offers a 1-hour cache at 2× input.anthropicopenai
  • So the real cost difference usually comes from the base model price and how often you actually hit the cache, not the caching mechanism alone.anthropic
  • In many cases, OpenAI’s underlying models are a bit cheaper, so the total bill can be lower even with similar caching terms.anthropic
  • Claude can win when you have large, stable prefixes reused many times within the cache window, because the 90% read discount amortizes the write cost quickly.anthropicopenai

Practical rule of thumb:

  • Choose OpenAI if you want lower risk, simpler automatic caching, or a cheaper comparable model.anthropicopenai
  • Choose Claude if you have very repetitive prompts, stable system/tool/doc prefixes, and high cache hit rates—especially in agentic or document-heavy workflows.anthropicopenaiopenai

One important caveat: if your prompts are dynamic or cache hits are unreliable, the cheaper option is often the one with the lower base model price, because cache savings may not materialize.anthropicopenai

So, in practice: OpenAI is often cheaper by default; Claude can be cheaper when caching is highly optimized and frequently reused.

Differences

The 3 models broadly agree – no notable differences found.

Best answerOpenAI

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Sources

  1. 1 Pricing - Anthropic docs.anthropic.com
  2. 2 Model guidance | OpenAI API developers.openai.com
  3. 3 GPT-5.4 Model | OpenAI API developers.openai.com
  4. 4 Compare models | OpenAI API developers.openai.com
  5. 5 GPT-5.6 Luna Model | OpenAI API developers.openai.com
  6. 6 Prompt Caching in the API | OpenAI openai.com
  7. 7 Streaming events | OpenAI API Reference platform.openai.com
  8. 8 Citações - Anthropic docs.anthropic.com
  9. 9 medium.com
  10. 10 respan.ai
  11. 11 openai.com
  12. 12 promnest.com
  13. 13 openai.com
  14. 14 technspire.com
  15. 15 cipherprojects.com
  16. 16 gingerlabs.ai
  17. 17 ofox.ai
  18. 18 edenai.co
  19. 19 platform.claude.com
  20. 20 developers.openai.com
  21. 21 developers.openai.com

Position Map

Where the models stand

Each row is one part of the answer. The cards show the distinct positions; the model chips show who supports each one.

0/100 Direction Shift · Stable
Models disagree

OpenAI provides a 50% discount on cached reads without write fees versus matching Claude's 90% read discount and 1.25x write fee.

Position 1

OpenAI provides a 50% discount and charges no write surcharge.

  • Gemini
Position 2

Older OpenAI models offer 50% off with no write fee, whereas newer models offer 90% off and some charge a 1.25x write fee.

  • DeepSeek
Position 3

OpenAI's current models match Claude with a 0.1x read price and 1.25x write surcharge.

  • OpenAI
See how each model moved across checks
Model position movement by watch date
ModelAug 11Aug 18Aug 25Sep 01
OpenAI
Grok — —
Gemini —
DeepSeek — — —
Same positionChanged position

Cite this answer

consens.io. (2026-08-18). Consensus answer to "Is Claude or OpenAI prompt caching cheaper in practice?". Models consulted: OpenAI: gpt-5.6-luna, Google Gemini: gemini-3.7-flash, Grok: grok-4.3-no-reasoning. Consensus model: OpenAI. Sources: https://docs.anthropic.com/en/docs/about-claude/pricing?4810b549_page=3&73cdfb14_page=2&939688b5_page=1&e768fcd2_page=2&utm_source=openai, https://developers.openai.com/api/docs/guides/latest-model?utm_source=openai, https://developers.openai.com/api/docs/models/gpt-5.4?utm_source=openai, https://developers.openai.com/api/docs/models/compare?utm_source=openai, https://developers.openai.com/api/docs/models/gpt-5.6-luna?utm_source=openai, https://openai.com/index/api-prompt-caching/?utm_source=openai, https://platform.openai.com/docs/api-reference/responses-streaming/response/refusal/delta?lang=curl&utm_source=openai, https://docs.anthropic.com/pt/docs/build-with-claude/citations?utm_source=openai, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGM1qtub2wIiVeSvood0nY_2-3iOj33l4by1U0cI-TgOzAByiqggCJEvUlk4p6nYAA6ZLD6Hf8gNDFmG1ECaL1VWqS59pXGVzrcCOv9snNpYvj-yVfsng9p37AL3G_Upj26AJFUdzOwcZR3TO_Y1qLXgiiuJy0vB8kSlzwkfkS4OzBZJmEh3N-5SPlptk9yCk2X0e9pZSPJrsGKDZlRVD6Bq6Cgv391b2cEzhkdfRjFfTuH, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEKUUdmvlDTnDG3zt8TVxL0F7hsKc7vbVlUrnj-Q1RjF4xM-kNn1hB3D9ekYg0f2KYMhu5Zgh-46IWqUHOwFriaWTh1eUOJDnKLWHVV3zvELSKfF2F9FJy-U_lQtmTMjbP3rdlCowlsPL7O, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFSSa2qx7RUDMvcbszfjF43Q2IEMcJ5ScrdWgW5jrhoLw_9jwEnd6HUS7xjWZTVOQA9SPODNSd9ARNZ4jyO9o0fb1DZJ7-1UzZwzaAqR1Ozwqb34FsNdzO6fOWLhJ1vmURg5w==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGb1hYaJP63ENFQS_hviozk6kagCK0UAh68ZBlBhwLGf8ebiDTvg9dKl9HdiErudGcAvGmXr8dMpMozzsUymkeLX_i8yURhPmnICxygMfa-rPRaPvTyJDT2xOrp0G2QVLtv18argyya67pbJYxqat8N3rpzfBN4j1kzd7PJCgDQ5sYT4V5l1Vdh6lGiCa48MnwVo3cxP4GH, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFPmg_BPL6-ZpHWjweWX82O6fml_qDMWexahXbDqEnDgkpMICiKpHUEZo-UaZohlc0ZmilqDKrsmIXoO1Lpeyrw_-iCCe54rARqwC1SJidzEyUDiMD0B6u_JPDrt_fGuCYWcXBo6s_foP5C-MHe3Tss-I0=, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE0fqfKcpeI-PwPPSEj0FmoKh6wcPW3N_GpqF9fh_r8sg3PX5gzJobFW4ZGfgDZwdiUHsM9twt98PQAtW-AFUFURdTVK4U3nP9bg0ivfuEPsUVSCh_8fVjSm8TZpk5gwQE6qsaei_XHaUXLOIkfNdqwl44cO57b4g==, https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE2tZD-WJUUmx-NpKMIoAmhzkDtaCJkxz77OMdFnV8ggn26TSj5t35I68fP3gToW7blyO2GIntLjgTevGyJg0rY4XEkSOnGfXFQRAPd9nx6d_VGq2sdu4MRGYE_dB_DDfo6OblHtS5KdzycEiqn4gITShYCvuFm3eg1aDCBSY5_9BD7ThgABeYTb2KxaA==, https://gingerlabs.ai/blog/openai-vs-anthropic-prompt-caching, https://ofox.ai/blog/prompt-caching-cost-math-anthropic-vs-openai-2026/, https://www.edenai.co/post/prompt-caching-claude-vs-gpt-vs-gemini-cost-playbook, https://platform.claude.com/docs/en/build-with-claude/prompt-caching, https://developers.openai.com/api/docs/pricing, https://developers.openai.com/api/docs/guides/prompt-caching Retrieved from https://www.consens.io/s/is-claude-or-openai-prompt-caching-cheaper-in-practice-KaTChmKxXX90G0vc?version=e3438a2682d7ba51e58af75b

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Consensus Watch

Run history

64/100 latest agreement
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Agreement over time

How strongly the models support the same claims. Every point links to its run below.

100 50 0 2026-08-11: 64/100 · No material movement 2026-08-18: 90/100 · Refined the pricing comparison to clarify that both providers offer similar cache read discounts (~90%) and that total cost differences often stem from underlying base model prices, while maintaining the same core conclusions regarding which provider to choose for different workload patterns. 2026-08-25: 75/100 · Restated, not moved: The consensus shifted from stating OpenAI is usually cheaper in default practice to clarifying that neither is universally cheaper. It adds explicit mathematical breakdowns, details on OpenAI's tiered cache read discounts (0.1x to 0.5x) vs. Claude's write premiums/5-minute window, and broader workload nuances. 2026-09-01: 64/100 · No material movement 2026-08-11 2026-09-01

Checks

Newest first. Open any saved result to read the full consensus from that date.

  1. 2026-09-01 Stable
    64/100 agreement

    No meaningful movement detected in this check.

    Open this consensus
  2. 2026-08-25 Stable
    75/100 agreement

    Restated, not moved: The consensus shifted from stating OpenAI is usually cheaper in default practice to clarifying that neither is universally cheaper. It adds explicit mathematical breakdowns, details on OpenAI's tiered cache read discounts (0.1x to 0.5x) vs. Claude's write premiums/5-minute window, and broader workload nuances.

    Open this consensus
  3. 2026-08-18 Meaningful change
    90/100 agreement

    Refined the pricing comparison to clarify that both providers offer similar cache read discounts (~90%) and that total cost differences often stem from underlying base model prices, while maintaining the same core conclusions regarding which provider to choose for different workload patterns.

    Open this consensus
  4. 2026-08-11 Stable
    64/100 agreement

    No meaningful movement detected in this check.

    Open this consensus

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About this tracked question

3 AI models answered this question independently on 2026-08-18. A judge from a different model family then cross-checked the answers, scored how far they agree and flagged where they differ. The question is re-checked weekly, and every earlier version stays on this page.

AI models can make mistakes – verify important information against the sources above.

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