Observed 30-day snapshot
Prompt caching can avoid repeatedly processing a stable prefix such as repository context, instructions, or tool definitions. This analysis ranks normalized model families by the share of their observed prompt-side tokens reported as cache reads. It is a usage-composition measurement—not a claim about provider-side hit logic, latency, or money saved.
What the data says
Cohort cached-input share
96.9%
Weighted by prompt-side tokens across eligible models.
Eligible-model median
95.6%
Each eligible model receives equal weight.
Observed cache reads
881.51B
Reported tokens served from an existing prompt cache.
Models meeting floor
54
At least 2 developers and 100.0K prompt-side tokens.
model-24d682bd5981
3 developers · 2.38B prompt-side tokens
minimax-m3
2 developers · 1.05B prompt-side tokens
gpt-6-sol
62 developers · 42.56B prompt-side tokens
deepseek-flash
4 developers · 3.16B prompt-side tokens
claude-opus-5
104 developers · 129.61B prompt-side tokens
claude-opus-5-5
116 developers · 309.70B prompt-side tokens
gpt-6.1-sol
71 developers · 58.09B prompt-side tokens
gpt-6-astra
102 developers · 82.38B prompt-side tokens
gpt-5.6-sol
77 developers · 43.96B prompt-side tokens
gpt-5.6-sol-high
2 developers · 1.95B prompt-side tokens
We calculate each model's cached-input share as cache-read tokens ÷ (uncached input + cache-write + cache-read tokens). A result of 75% means three quarters of the measured prompt-side tokens were reported as reads from an existing cache. Output tokens are outside that denominator.
A high cached-input share can indicate that long, stable prefixes are being reused. It can also reflect a particular agent architecture, session length, provider reporting format, or a small number of very large cached contexts. The ratio does not tell us whether the reused context was relevant or whether a shorter prompt would have been more efficient.
Savings depend on the provider's dated cache-read and cache-write prices, cache lifetime, write frequency, and ordinary input rate. Some providers charge extra to create a cache. Use the linked savings calculator with your own rates before turning this observed share into a budget estimate.
Window. The page requests the current 30-day aggregate. The snapshot timestamp is displayed above. Counts come from daily usage rows belonging to listed developers and exclude rows held from public rankings.
Normalization. Date-suffixed and gateway-prefixed raw model identifiers are merged into normalized model families before token buckets and distinct developers are counted.
Sample floors and coverage. A model must have at least 2 distinct participating developers and 100,000 combined uncached-input, cache-write, and cache-read tokens. The API returns at most 60 models ranked by total tokens, so ratio leaders are leaders among returned rows meeting the floor. These rules reduce one-person and tiny-denominator artifacts; they do not make the cohort statistically representative.
Reporting limits. Token categories are taken from agent/provider usage records and may not be reported consistently by every integration. A zero cache-read value can mean no observed cache reuse or unavailable cache telemetry; this aggregate cannot distinguish those cases.
Cohort limit. Public participation is opt-in. Results describe this cohort's coding sessions, not market share or a survey of all AI developers. They should be treated as directional observed behavior.
Aggregated model, agent, trend, skill, and tool-call totals from participating developers.
Explains what the CLI aggregates, what it does not collect, and the limits of the public cohort.
| 62 |
| deepseek-flash | 98.0% | 3.10B | 0 | 64.8M | 4.8M | 4 |
| claude-opus-5 | 97.8% | 126.82B | 2.78B | 9.1M | 477.8M | 104 |
| claude-opus-5-5 | 97.6% | 302.30B | 7.39B | 3.2M | 944.8M | 116 |
| gpt-6.1-sol | 97.4% | 56.57B | 79.8K | 1.52B | 224.1M | 71 |
| gpt-6-astra | 97.3% | 80.14B | 143.9K | 2.24B | 268.3M | 102 |
| gpt-5.6-sol | 97.2% | 42.72B | 2.5M | 1.24B | 137.9M | 77 |
| gpt-5.6-sol-high | 97.1% | 1.90B | 40.2M | 16.5M | 5.1M | 2 |
| gpt-6-luna | 97.1% | 15.54B | 25.0M | 439.6M | 72.7M | 69 |
| gpt-5.6-luna | 97.1% | 12.51B | 1.6M | 374.0M | 33.3M | 59 |
| gpt-5.6-sol-medium | 97.0% | 1.05B | 28.7M | 3.8M | 2.3M | 5 |
| claude-fable-5-1 | 96.9% | 28.84B | 913.5M | 7.3M | 127.0M | 67 |
| claude-sonnet-5-5 | 96.9% | 38.28B | 1.23B | 922.2K | 167.2M | 74 |
| glm-5.3 | 96.8% | 1.54B | 0 | 51.0M | 4.7M | 11 |
| claude-sonnet-5 | 96.8% | 44.08B | 1.45B | 8.8M | 180.0M | 92 |
| grok-bot-cua | 96.7% | 4.17B | 111.4M | 29.9M | 11.5M | 20 |
| gpt-5.6-terra | 96.7% | 8.43B | 0 | 290.8M | 26.2M | 58 |
| model-5c8393b7aaa1 | 96.4% | 502.6M | 0 | 18.6M | 3.3M | 4 |
| deepseek-v4.1-flash | 96.4% | 4.68B | 1.5M | 173.4M | 28.9M | 17 |
| muse-spark-1.3-contributor | 96.3% | 412.2M | 0 | 15.9M | 554.5K | 2 |
| mimo-v2.5-free | 96.1% | 295.1M | 0 | 11.9M | 1.3M | 5 |
| cursor-grok-4.6-xhigh-fast | 96.1% | 390.4M | 0 | 16.0M | 2.5M | 6 |
| claude-opus-5-thinking-high | 96.0% | 245.6M | 8.8M | 1.4M | 1.9M | 3 |
| composer-2.5 | 95.9% | 875.9M | 0 | 37.0M | 5.2M | 9 |
| grok-4.7-high-fast | 95.6% | 999.6M | 0 | 45.9M | 6.6M | 17 |
| composer-2.5-fast | 95.6% | 641.7M | 0 | 29.6M | 4.4M | 21 |
| grok-4.7-high | 95.4% | 969.5M | 0 | 46.5M | 3.8M | 11 |
| nemotron-3-ultra-550b-a55b | 95.2% | 543.4M | 0 | 27.2M | 1.2M | 3 |
| muse-spark-1.3-contributor-free | 95.1% | 4.74B | 0 | 242.9M | 9.8M | 27 |
| cursor-grok-4.6-high-fast | 95.1% | 2.67B | 0 | 136.8M | 13.7M | 19 |
| big-pickle | 94.9% | 334.1M | 0 | 17.8M | 2.0M | 17 |
| space-bunny-free | 94.5% | 3.35B | 204.0K | 194.7M | 11.0M | 15 |
| claude-fable-5 | 94.2% | 1.60B | 92.7M | 5.4M | 8.7M | 10 |
| mimo-v2.6-flash-free | 94.2% | 495.2M | 0 | 30.4M | 3.1M | 10 |
| claude-opus-4-8 | 93.8% | 8.00B | 524.7M | 6.3M | 39.0M | 43 |
| cursor-grok-4.6-high | 93.6% | 1.70B | 0 | 116.7M | 9.6M | 11 |
| claude-haiku-4-5-20251001 | 93.1% | 1.93B | 142.8M | 277.9K | 16.5M | 57 |
| default | 92.7% | 4.65B | 24.6M | 341.8M | 27.2M | 20 |
| claude-opus-4-6 | 92.3% | 5.63B | 466.4M | 610.9K | 15.7M | 11 |
| cursor-grok-4.5-high-fast | 92.0% | 339.8M | 0 | 29.4M | 2.9M | 8 |
| claude-haiku-5-5 | 92.0% | 251.3M | 21.8M | 5.4K | 2.6M | 27 |
| cursor-grok-4.6-xhigh | 90.6% | 400.6M | 0 | 41.6M | 4.1M | 7 |
| claude-sonnet-4-6 | 90.1% | 4.09B | 446.9M | 9.2K | 5.5M | 11 |
| gpt-5.5 | 90.1% | 7.07B | 0 | 775.5M | 10.8M | 69 |
| glm-5.3-flash | 89.9% | 1.15B | 79.2K | 129.1M | 3.6M | 11 |
| claude-opus-4-7 | 89.1% | 407.3M | 49.9M | 10.6K | 5.1M | 10 |
| grok-bot-default | 86.7% | 4.18B | 188.8M | 455.6M | 27.8M | 25 |
| deepseek-v4-flash | 86.6% | 702.5M | 0 | 108.7M | 2.7M | 8 |
| grok-bot-automation | 84.8% | 2.72B | 132.2M | 354.2M | 32.5M | 17 |
| mimo-v2.6-pro | 83.2% | 344.0M | 182.6K | 69.3M | 1.7M | 5 |
| cursor-grok-4.6-medium | 83.0% | 645.1M | 0 | 132.2M | 4.1M | 16 |
| gemini-3.8-flash | 25.7% | 393.4M | 0 | 1.14B | 5.9M | 7 |