Requesty

Prompt cache hit rate by provider · June 2026

DeepSeek served 85.5% of input tokens from cache in June 2026, the highest among major providers. The median major provider served 55.2%.

Share of input tokens served from the provider's prompt cache, per provider and month.

Data through June 30, 2026Updated November 11, 2026
This is the permanent snapshot for June 2026. See the latest month (October 2026)

Cache hit rate, June 2026

Source: Requesty production gateway
  • DeepSeek85.5%
  • Anthropic84.9%
  • Fireworks84.7%
  • Vertex (Claude)73.0%
  • Bedrock67.7%
  • Azure65.0%
  • OpenAI45.5%
  • DeepInfra38.3%
  • xAI36.9%
  • Mistral32.4%
  • Vertex (Gemini)26.7%
  • Novita23.1%

Key findings

  1. 01DeepSeek leads at 85.5%; Novita is lowest at 23.1%.
  2. 023 of 12 major providers served at least 80% of input tokens from cache.
  3. 03DeepInfra moved the most since May 2026: cache hit rate went from 12.6% to 38.3% (+25.7 pp).

Cache hit rate by month

0.0%23.1%46.2%69.3%92.3%May 26Jun 26DeepSeek, May 26: 83.8%DeepSeek, Jun 26: 85.5%Anthropic, May 26: 80.6%Anthropic, Jun 26: 84.9%Fireworks, May 26: 84.3%Fireworks, Jun 26: 84.7%Vertex (Claude), May 26: 49.1%Vertex (Claude), Jun 26: 73.0%Bedrock, May 26: 45.7%Bedrock, Jun 26: 67.7%Azure, May 26: 67.7%Azure, Jun 26: 65.0%
DeepSeekAnthropicFireworksVertex (Claude)BedrockAzure

What changed since May 2026

  • DeepInfra12.6% → 38.3% (+25.7 pp)
  • Vertex (Claude)49.1% → 73.0% (+23.9 pp)
  • Bedrock45.7% → 67.7% (+22.0 pp)
  • Novita5.3% → 23.1% (+17.8 pp)
  • OpenAI36.0% → 45.5% (+9.5 pp)

What to do about it

  • Keep the system prompt and tool definitions at the start of the request and unchanged between turns.
  • On providers that need explicit cache markers, set them. Without them the hit rate stays near zero.

Requesty adds cache markers automatically for providers that need them.

Read about prompt caching

Data

ProviderCache hit rateTraffic shareOrganizations (band)
DeepSeek85.50%8.00%100-499
Anthropic84.89%24.40%500+
Fireworks84.70%0.73%100-499
Vertex (Claude)73.03%2.83%100-499
Bedrock67.71%3.82%500+
Azure64.97%5.39%100-499
OpenAI45.46%30.70%500+
DeepInfra38.33%1.73%100-499
xAI36.92%1.09%100-499
Mistral32.36%0.86%100-499
Vertex (Gemini)26.66%17.84%500+
Novita23.05%0.96%100-499

12 rows published. Rows below the floors are withheld.

Questions this answers

Which LLM provider has the highest prompt cache hit rate?
DeepSeek served 85.5% of input tokens from cache in June 2026, the highest among major providers. The median major provider served 55.2%.
What is a typical prompt caching hit rate in production?
DeepSeek served 85.5% of input tokens from cache in June 2026, the highest among major providers. The median major provider served 55.2%.
How much of my input is served from cache on Anthropic, OpenAI or Bedrock?
DeepSeek served 85.5% of input tokens from cache in June 2026, the highest among major providers. The median major provider served 55.2%.

Method and definitions

  • Cache hit rate is cached input tokens divided by input tokens, the same definition /rankings uses.
  • Providers that report no cached tokens are left out of the chart. Only providers with at least 0.5% of published traffic are shown.
  • A row is published only when it has at least 20 requests, at least 5 distinct organizations, and no single organization above 80% of its traffic. These are the same floors /rankings uses. Rows below the floors are withheld, not estimated.
  • Only shares, rates, medians and organization bands are published. Absolute request, token and spend totals stay private.
Cache hit rate:
Cached input tokens / input tokens, summed over the month.

Per-model numbers with the same definitions are on /rankings, refreshed weekly.

Caveats

  • Hit rate depends on workload. Long agent sessions with a stable prefix cache far better than one-off requests.
  • Providers report cached tokens differently. Some only count explicit cache reads.

Revision history and other months

Cite and reuse

Free to reuse under CC BY 4.0. Credit "Requesty Data" and link to this page. Cite the month URL so the numbers you quote stay fixed.

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