{
 "measurement": "Does the Claude Code prompt cache actually expire after five minutes of inactivity",
 "claude_code_version": "2.1.229",
 "auth": "Claude subscription. No ANTHROPIC_API_KEY or ANTHROPIC_AUTH_TOKEN in the environment, no ANTHROPIC_BASE_URL and no apiKeyHelper in any settings file. service_tier reported as standard on every call.",
 "claim_under_test": "From circulating guides: \"If the cache expires (after 5 minutes of inactivity), the next request is treated as a cache miss. Claude re-processes and re-caches the full prefix, billed at the higher cache write rate (1.25x standard)\", with a claimed 20-32% increase in cache creation costs. GitHub issue #46829 claims Anthropic \"silently changed the prompt cache TTL default from 1 hour to 5 minutes sometime in early March 2026\"; it was closed as not planned. The issue also claims a 17.1% total overpayment across three months, derived from the aggregate 5m/1h token split across 119,866 session-JSONL API calls. Issue URL: https://github.com/anthropics/claude-code/issues/46829",
 "what_the_docs_say": "https://code.claude.com/docs/en/prompt-caching : \"On a Claude subscription, Claude Code requests the one-hour TTL automatically, so the cache survives breaks of up to an hour.\" An API key or third-party provider stays at five minutes, and FORCE_PROMPT_CACHING_5M=1 forces the short TTL regardless. The docs name TWO routes by which a subscription still gets the five-minute cache: exceeding the plan limit and drawing on usage credits, and subagents, which \"use the five-minute TTL even on a subscription, since the automatic one-hour TTL applies to the main conversation\". ENABLE_PROMPT_CACHING_1H=1 overrides the first.",
 "method": {
  "shape": "Three turns in one resumed session. Turn 1 reads a ~40KB file carrying a planted marker. Turn 2 echoes the marker back. The IDLE GAP goes here. Turn 3 asks for the marker again and is the measured turn.",
  "why_the_gap_goes_before_turn_3": "A first version put the gap before turn 2 and was blind; its own positive control caught it. The FIRST resume always writes a new cache breakpoint over the grown conversation, identically at 5s, 60s and 480s, so turn 2 can never respond to a gap. Turn 3 is the turn that is nearly free when the cache is alive (39 tokens written) and a full rebuild when it is dead (17,613), which is the separation the measurement needs.",
  "arms": {
   "warm": "60s gap, default TTL. Baseline.",
   "cold": "480s gap, default TTL. The question: does an eight-minute break lose the cache?",
   "forced_5m": "480s gap, FORCE_PROMPT_CACHING_5M=1. THE POSITIVE CONTROL. If the default arm keeps its cache and this one keeps it too, the instrument cannot see expiry and the corpus is void."
  },
  "metric": "cacheCreationInputTokens on turn 3. Totals from modelUsage. The per-TIER split is not in modelUsage at all and is summed from usage.iterations[].cache_creation.",
  "controls": {
   "arrival": "Both turn 2 and turn 3 must echo the planted marker as an exact string. 15 of 15 on both.",
   "expiry_positive_control": "The forced_5m arm, published per run rather than asserted. It rebuilt in 5 of 5.",
   "flag": "FORCE_PROMPT_CACHING_5M asserted PRESENT in the child environment for the forced arm and ABSENT for the other two. The WRITE TIER is published per run to show the flag took effect, and a separate pre-run control is published in full under flag_control below.",
   "session": "Turn 1's session id passed to --resume and turn 3's own reported id compared back. Same session in 15 of 15.",
   "isolation": "--setting-sources project on every call, asserted onto the command line.",
   "clock": "The real elapsed gap measured per run, not assumed.",
   "no_exclusions": "All 15 runs are scored."
  }
 },
 "known_limits": {
  "eight_minutes_not_an_hour": "CLOSED 2026-08-13 by one_hour_bracket above: the default cache kept its prefix across a 55-minute gap (39 tokens written, 3 of 3) and lost it across a 70-minute gap (17,622 written, 3 of 3), which matches the documented one-hour TTL. The boundary is bracketed, not located.",
  "subscription_only": "Measured on subscription auth. The docs say an API key, Amazon Bedrock, Google Cloud's Agent Platform, Microsoft Foundry and Claude Platform on AWS all default to the five-minute TTL. Untested here, and on those the circulating advice would apply as written.",
  "usage_credit_downgrade_untested": "The docs state that a subscription over its plan limit and drawing on usage credits automatically drops to the five-minute TTL. That is a plausible route by which real users saw real cost increases, and it is NOT measured here. No claim is made about why anyone else's costs moved.",
  "not_a_historical_claim": "Measured on 2026-08-13 against 2.1.229. Says nothing about what the default was in March 2026, which is what issue #46829 alleges.",
  "control_arm_prefix_differs_by_0_4_percent": "The working directory is embedded in the system prompt, so the longer forced_5m directory name made its established prefix 33,670 tokens against 33,536, a 0.4% difference. The cold arm is 33,536 in all five runs; the warm arm is 33,536 in four and 33,528 in one, so the default arms agree with each other to within 8 tokens rather than being byte-identical. No direction is argued for this confound. What is measured is that the forced arm touched MORE tokens than the default arm on every one of the three turns (56,200 against 55,935, 33,672 against 33,538, 33,711 against 33,577), and that it still cost less over the session. The harness now pads arm directory names to equal width.",
  "first_design_is_not_published": "The post describes a discarded first design in which the gap sat before turn 2 and every arm came back flat. That corpus was not kept and is NOT published here. What IS published is design_diagnostic, a single run showing turn 2 writing ~17.5k at a five-second gap, which is the checkable part of that story.",
  "tier_split_covers_one_api_call_per_turn": "usage.iterations carries one entry per API call of the LAST model turn, so on turn 1 (two model turns) the summed tier split is 11,624 against a modelUsage cache_creation of 17,535 and does not reconcile. On the measured turn 3 it reconciles exactly (39 = 39, and 17,613 = 17,613). Tier figures quoted in the post are turn 3's for that reason."
 },
 "marker_prefix": "TTLQ",
 "gap_short_s": 60,
 "gap_long_s": 480,
 "results": {
  "warm": {
   "runs": 5,
   "gap_s_median": 60.0,
   "turn3_cache_read_median": 33536,
   "turn3_cache_read_min": 33528,
   "turn3_cache_creation_median": 39,
   "turn3_cache_creation_min": 39,
   "turn3_cache_creation_max": 39,
   "prefix_established_median": 33536,
   "runs_that_kept_the_cache": "5 of 5",
   "verdict": "kept in every run",
   "turn1_tier_1h_median": 11624,
   "turn1_tier_5m_median": 0,
   "flag_control_ok": "5 of 5",
   "turn1_context_median": 55935,
   "cost_turn3_median": 0.017418000000000003
  },
  "cold": {
   "runs": 5,
   "gap_s_median": 480.0,
   "turn3_cache_read_median": 33536,
   "turn3_cache_read_min": 33536,
   "turn3_cache_creation_median": 39,
   "turn3_cache_creation_min": 39,
   "turn3_cache_creation_max": 39,
   "prefix_established_median": 33536,
   "runs_that_kept_the_cache": "5 of 5",
   "verdict": "kept in every run",
   "turn1_tier_1h_median": 11624,
   "turn1_tier_5m_median": 0,
   "flag_control_ok": "5 of 5",
   "turn1_context_median": 55935,
   "cost_turn3_median": 0.017418000000000003
  },
  "forced_5m": {
   "runs": 5,
   "gap_s_median": 480.0,
   "turn3_cache_read_median": 16096,
   "turn3_cache_read_min": 16096,
   "turn3_cache_creation_median": 17613,
   "turn3_cache_creation_min": 17613,
   "turn3_cache_creation_max": 17613,
   "prefix_established_median": 33670,
   "runs_that_kept_the_cache": "0 of 5",
   "verdict": "lost in every run",
   "turn1_tier_1h_median": 0,
   "turn1_tier_5m_median": 11627,
   "flag_control_ok": "5 of 5",
   "turn1_context_median": 56200,
   "cost_turn3_median": 0.11838925
  },
  "totals": {
   "runs": 15,
   "scored": 15,
   "arrival_control": "15 of 15 echoed the planted marker on BOTH the setup turn and the measured turn",
   "same_session": "15 of 15",
   "cold_threshold_tokens": 1000,
   "turn1_prefix_spread": "55,935 to 56,200 tokens across arms"
  },
  "session_economics": {
   "note": "The headline 6.8x is ONE turn of three. Summed across the whole session the sign reverses, because one-hour cache writes bill at 2x list and five-minute writes at 1.25x. The first draft of the post missed this and an adversarial pass caught it.",
   "per_arm": {
    "warm": {
     "cost_turn1_median": 0.19857450000000001,
     "cost_turn2_median": 0.1838955,
     "cost_turn3_median": 0.017418000000000003,
     "cost_session_median": 0.399888,
     "cost_session_min": 0.399524,
     "cost_session_max": 0.399888,
     "cache_creation_all_three_turns": 35139,
     "cache_read_all_three_turns": 87370,
     "prefix_established_distinct": [
      33528,
      33536
     ]
    },
    "cold": {
     "cost_turn1_median": 0.19857450000000001,
     "cost_turn2_median": 0.1838955,
     "cost_turn3_median": 0.017418000000000003,
     "cost_session_median": 0.399888,
     "cost_session_min": 0.399888,
     "cost_session_max": 0.399888,
     "cache_creation_all_three_turns": 35139,
     "cache_read_all_three_turns": 87370,
     "prefix_established_distinct": [
      33536
     ]
    },
    "forced_5m": {
     "cost_turn1_median": 0.13307750000000002,
     "cost_turn2_median": 0.11814549999999999,
     "cost_turn3_median": 0.11838925,
     "cost_session_median": 0.369612,
     "cost_session_min": 0.369612,
     "cost_session_max": 0.369617,
     "cache_creation_all_three_turns": 52731,
     "cache_read_all_three_turns": 70311,
     "prefix_established_distinct": [
      33670
     ]
    }
   },
   "forced_vs_default_session_ratio": 0.9243,
   "separated": true,
   "reading": "Forcing the five-minute TTL made this three-turn session 7.6% CHEAPER, and every forced run beat every default run. The forced arm also WROTE 50% more cache (52,731 tokens against 35,139) and still cost less, which isolates the cause to the write rate rather than the volume.",
   "what_it_does_not_establish": "The break-even. This corpus contains exactly ONE session shape: three turns, a ~33,500-token prefix and a single eight-minute break. No run varies the number of breaks or the size of the prefix. Where the balance flips for a different shape is not measured here and NO DIRECTION is claimed for it."
  }
 },
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 ],
 "design_diagnostic": {
  "note": "A SINGLE one-off run, not part of the 15 scored runs below, kept here because the post quotes it. It is the run that showed the first design was blind and located the sensitive turn.",
  "sequence": "one session, 5-second gaps between every turn, ~40KB file read on turn 1",
  "turn1": {
   "cache_read": 37853,
   "cache_creation": 17519
  },
  "turn2_gap_5s": {
   "cache_read": 15971,
   "cache_creation": 17548
  },
  "turn3_gap_5s": {
   "cache_read": 33519,
   "cache_creation": 31
  },
  "what_it_shows": "Turn 2 writes ~17.5k at a 5-SECOND gap, the same as it writes at 480 seconds, so turn 2 is gap-independent and cannot measure a TTL. Turn 3 writes 31 tokens. That is why the measured turn in this corpus is turn 3."
 },
 "flag_control": {
  "note": "Pre-run control that FORCE_PROMPT_CACHING_5M=1 moves the write tier. Two single-turn runs on the same trivial prompt, in directories with GENUINELY equal-length names (the earlier version of this control used 9- and 8-character names, which is why its prefixes did not match).",
  "default": {
   "env_forced_5m": false,
   "dir_name_len": 8,
   "cache_creation": 5897,
   "cache_read": 15976,
   "tokens_touched": 22396,
   "tier_1h_created": 5897,
   "tier_5m_created": 0
  },
  "forced_5m": {
   "env_forced_5m": true,
   "dir_name_len": 8,
   "cache_creation": 5897,
   "cache_read": 16101,
   "tokens_touched": 22521,
   "tier_1h_created": 0,
   "tier_5m_created": 5897
  },
  "verdict": {
   "tier_inverted": true,
   "prefix_sizes_equal": true,
   "tokens_touched_delta": 125
  }
 },
 "cost_model_reconciliation": {
  "note": "The write-rate mechanism is NOT asserted from a price list, it is recovered from this corpus's own published cost figures. Applying per-Mtok rates of $5 base input, $25 output, $0.50 cache read, $6.25 five-minute cache write and $10 one-hour cache write to the measured turn leaves a residual of exactly $0.000250 in every arm, which is exactly 10 output tokens. That the residual is identical and a clean integer across arms with wildly different cache splits is what confirms the rates.",
  "rates_per_mtok": {
   "base_input": 5.0,
   "output": 25.0,
   "cache_read": 0.5,
   "cache_write_5m_tier": 6.25,
   "cache_write_1h_tier": 10.0
  },
  "the_premium": "The one-hour tier writes at 2.0x the base input rate; the five-minute tier writes at 1.25x. That 0.75x-of-base difference on every written token is the whole mechanism behind the session-total reversal.",
  "measured_turn_per_arm": [
   {
    "arm": "warm",
    "input": 2,
    "cache_read": 33536,
    "written_1h_tier": 39,
    "written_5m_tier": 0,
    "predicted_usd": 0.017168,
    "published_usd": 0.017418000000000003,
    "residual_usd": 0.00025,
    "residual_as_output_tokens_at_25_per_mtok": 10.0
   },
   {
    "arm": "cold",
    "input": 2,
    "cache_read": 33536,
    "written_1h_tier": 39,
    "written_5m_tier": 0,
    "predicted_usd": 0.017168,
    "published_usd": 0.017418000000000003,
    "residual_usd": 0.00025,
    "residual_as_output_tokens_at_25_per_mtok": 10.0
   },
   {
    "arm": "forced_5m",
    "input": 2,
    "cache_read": 16096,
    "written_1h_tier": 0,
    "written_5m_tier": 17613,
    "predicted_usd": 0.118139,
    "published_usd": 0.11838925,
    "residual_usd": 0.00025,
    "residual_as_output_tokens_at_25_per_mtok": 10.0
   }
  ],
  "scope_warning": "The rate model reconciles on the MEASURED TURN ONLY. Turns 1 and 2 make more than one API call and usage.iterations carries only the last one, so their tier splits undercount and the model must not be applied to them. Reconstructing a whole session from these rates gives $0.331 against a published $0.370 for the forced arm, which is the undercount, not a pricing discovery. Session comparisons in the post use the PUBLISHED per-turn costs, never the reconstructed ones."
 },
 "one_hour_bracket": {
  "added": "2026-08-13, after the 15 runs below were published. It closes the known limit 'eight_minutes_not_an_hour'.",
  "question": "The docs say a subscription cache 'survives breaks of up to an hour'. The main corpus only showed survival past eight minutes. This brackets the documented boundary.",
  "design": "Identical harness and three-turn shape. Three independent processes, each running all three arms once, so every cell has 3 runs. Arm directory names are padded to equal width in this run.",
  "arms": {
   "55_minutes_default_ttl": {
    "gap_s": 3300,
    "runs": 3,
    "turn3_cache_creation": [
     39
    ],
    "turn3_cache_read": [
     33554
    ],
    "verdict": "kept in 3 of 3"
   },
   "70_minutes_default_ttl": {
    "gap_s": 4200,
    "runs": 3,
    "turn3_cache_creation": [
     17622
    ],
    "turn3_cache_read": [
     15971
    ],
    "verdict": "LOST in 3 of 3"
   },
   "70_minutes_forced_5m": {
    "gap_s": 4200,
    "runs": 3,
    "turn3_cache_creation": [
     17616
    ],
    "turn3_cache_read": [
     16096
    ],
    "verdict": "LOST in 3 of 3"
   }
  },
  "reading": "The default cache survived 55 minutes writing 39 tokens and was gone by 70 minutes, rebuilding 17,622. That matches the documented one-hour TTL. It also supplies something the main corpus could not: expiry observed on the DEFAULT arm, so the eight-minute survival there is not an artifact of an instrument that can only see expiry when the flag is forced.",
  "controls": {
   "arrival": "9 of 9 echoed the planted marker on both the setup turn and the measured turn",
   "same_session": "9 of 9",
   "no_exclusions": "all 9 runs scored",
   "gaps_measured": "3300.0s and 4200.0s actual, not assumed"
  },
  "known_limits": {
   "boundary_not_narrowed": "This brackets the boundary between 55 and 70 minutes. It does not locate it, and does not test whether it sits exactly at 60. Three runs per cell.",
   "one_shape": "Same single session shape as the main corpus."
  },
  "runs": [
   {
    "arm": "warm",
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