China's daily token calls hit 175 trillion in June.
Over 1,000x the start of 2024.
Inference volume has now passed training for the first time.
At $0.10 per million tokens, 175T a day is $17.5M a day.
Training budgets don't explain that bill.
Inference does. #InferenceCost
Over 1,000x the start of 2024.
Inference volume has now passed training for the first time.
At $0.10 per million tokens, 175T a day is $17.5M a day.
Training budgets don't explain that bill.
Inference does. #InferenceCost
November 1, 2026 at 7:02 PM
China's daily token calls hit 175 trillion in June.
Over 1,000x the start of 2024.
Inference volume has now passed training for the first time.
At $0.10 per million tokens, 175T a day is $17.5M a day.
Training budgets don't explain that bill.
Inference does. #InferenceCost
Over 1,000x the start of 2024.
Inference volume has now passed training for the first time.
At $0.10 per million tokens, 175T a day is $17.5M a day.
Training budgets don't explain that bill.
Inference does. #InferenceCost
Kimi reset 25% of each K3.1 Pro subscriber's monthly quota —
a week of usage.
That reads like a capacity problem.
The fix was fewer subagent calls and shorter output:
tokens per task, not per token.
Capacity was fine. Cost per task was not. #InferenceCost
a week of usage.
That reads like a capacity problem.
The fix was fewer subagent calls and shorter output:
tokens per task, not per token.
Capacity was fine. Cost per task was not. #InferenceCost
October 27, 2026 at 12:23 AM
Kimi reset 25% of each K3.1 Pro subscriber's monthly quota —
a week of usage.
That reads like a capacity problem.
The fix was fewer subagent calls and shorter output:
tokens per task, not per token.
Capacity was fine. Cost per task was not. #InferenceCost
a week of usage.
That reads like a capacity problem.
The fix was fewer subagent calls and shorter output:
tokens per task, not per token.
Capacity was fine. Cost per task was not. #InferenceCost
ICYMI: Explaining inference cost #AI #MachineLearning #InferenceCost #ArtificialIntelligence #TokenEconomy
Explaining inference cost
Inference cost is the compute and money spent each time a trained AI model answers a request. How it is priced per token, who pays it, and why ads now fund it.
ppc.land
October 17, 2026 at 7:29 PM
ICYMI: Explaining inference cost #AI #MachineLearning #InferenceCost #ArtificialIntelligence #TokenEconomy
ICYMI: Explaining inference cost #AI #MachineLearning #InferenceCost #ArtificialIntelligence #TokenEconomy
Explaining inference cost
Inference cost is the compute and money spent each time a trained AI model answers a request. How it is priced per token, who pays it, and why ads now fund it.
ppc.land
October 17, 2026 at 7:31 PM
ICYMI: Explaining inference cost #AI #MachineLearning #InferenceCost #ArtificialIntelligence #TokenEconomy
Qwen's new image checkpoint runs 8 denoising steps instead of 40.
Same 7B model, same 2K output — but 5x fewer forward passes.
A prefix cache computes the references once, then reuses them.
Steps, not parameters, are what the GPU is metered in. #InferenceCost
Same 7B model, same 2K output — but 5x fewer forward passes.
A prefix cache computes the references once, then reuses them.
Steps, not parameters, are what the GPU is metered in. #InferenceCost
October 9, 2026 at 9:49 PM
Qwen's new image checkpoint runs 8 denoising steps instead of 40.
Same 7B model, same 2K output — but 5x fewer forward passes.
A prefix cache computes the references once, then reuses them.
Steps, not parameters, are what the GPU is metered in. #InferenceCost
Same 7B model, same 2K output — but 5x fewer forward passes.
A prefix cache computes the references once, then reuses them.
Steps, not parameters, are what the GPU is metered in. #InferenceCost
Anthropic's Claude pushed a physics record from 8 loops to 9.
Independently verified. The number to keep isn't the loop count.
Run cost: ~$1,000–2,000 of inference. One method: ~$100.
That $100 equals 96 CPU-weeks.
A price tag, not a compute budget. #InferenceCost
Independently verified. The number to keep isn't the loop count.
Run cost: ~$1,000–2,000 of inference. One method: ~$100.
That $100 equals 96 CPU-weeks.
A price tag, not a compute budget. #InferenceCost
September 25, 2026 at 10:10 PM
Anthropic's Claude pushed a physics record from 8 loops to 9.
Independently verified. The number to keep isn't the loop count.
Run cost: ~$1,000–2,000 of inference. One method: ~$100.
That $100 equals 96 CPU-weeks.
A price tag, not a compute budget. #InferenceCost
Independently verified. The number to keep isn't the loop count.
Run cost: ~$1,000–2,000 of inference. One method: ~$100.
That $100 equals 96 CPU-weeks.
A price tag, not a compute budget. #InferenceCost
엔비디아 대항마 ZML 인퍼런스 비용 줄이는 3가지 방법
https://bit.ly/4veBSvj
#엔비디아 #ZML #인공지능 #인퍼런스비용 #NVIDIA #AI #InferenceCost
https://bit.ly/4veBSvj
#엔비디아 #ZML #인공지능 #인퍼런스비용 #NVIDIA #AI #InferenceCost
엔비디아 대항마 ZML 인퍼런스 비용 줄이는 3가지 방법 - 천의무봉
최근 인공지능 모델을 실제 서비스에 적용하려는 기업들이 가장 골치를 앓는 부분이 바로 인퍼런스 비용입니다. 학습을 마친 모델을 실제로 구동할 때 발생하는 이 비용은 서비스 규모가 �질수록 걷잡을 수 없이 커지곤 합니다. 프랑스의 핫한 스타트업 ZML이 최근 다양한 칩 환경에서 모델
blog.hangadac.com
July 8, 2026 at 9:53 AM
엔비디아 대항마 ZML 인퍼런스 비용 줄이는 3가지 방법
https://bit.ly/4veBSvj
#엔비디아 #ZML #인공지능 #인퍼런스비용 #NVIDIA #AI #InferenceCost
https://bit.ly/4veBSvj
#엔비디아 #ZML #인공지능 #인퍼런스비용 #NVIDIA #AI #InferenceCost
OpenAI just bragged they’ve slashed inference costs by 50% for guest ChatGPT users. Imagine faster answers without the price tag—what’s next for LLMs? Dive in to see the details. #OpenAI #InferenceCost #ChatGPTGuest
🔗 aidailypost.com/news/openai-...
🔗 aidailypost.com/news/openai-...
June 30, 2026 at 10:19 PM
OpenAI just bragged they’ve slashed inference costs by 50% for guest ChatGPT users. Imagine faster answers without the price tag—what’s next for LLMs? Dive in to see the details. #OpenAI #InferenceCost #ChatGPTGuest
🔗 aidailypost.com/news/openai-...
🔗 aidailypost.com/news/openai-...
Most LLM guidelines obsess over training spend, but real‑world teams run out of inference budget fast. Discover why the Train‑to‑Test scaling gap matters for deployment and how to budget smarter. #LLM #InferenceCost #ModelDeployment
🔗 aidailypost.com/news/standar...
🔗 aidailypost.com/news/standar...
April 17, 2026 at 6:14 PM
Most LLM guidelines obsess over training spend, but real‑world teams run out of inference budget fast. Discover why the Train‑to‑Test scaling gap matters for deployment and how to budget smarter. #LLM #InferenceCost #ModelDeployment
🔗 aidailypost.com/news/standar...
🔗 aidailypost.com/news/standar...