A Surprise in AI Token Usage and Costs

Matthew Berman reacts to a rising usage bill and notes why monitoring token consumption matters.

MBMatthew BermanPonente · Forward Future
Canal
Matthew Berman
Publicado
2 mar 2026
Vídeo
0:24
Lectura
1 min
Original
inglés
Abrir en YouTube
Al desplazarte, el vídeo se reduce a la esquina inferior derecha y sigue reproduciéndose. Los subtítulos siguen tu idioma de lectura.
Idioma de lecturaDisponible en 2 idiomas
Este artículo aún no está en español, así que se muestra el original en inglés.
RESUMEN

En 30 segundos

Matthew Berman checks a usage display and says the previous day cost about $130 and the current day had reached $32 by 9:30 a.m. He notes 70 million tokens for the earlier period and 25 million so far that day. The clip does not identify the service, model, pricing or full billing period.

  1. 1An unexpected billBerman reacts with surprise to the reported usage cost.
  2. 2Daily costsHe says the previous day cost about $130 and the current day was already at $32.
  3. 3Token usageHe cites 70 million tokens and 25 million so far that morning; the clip does not specify model or rate.

Conclusiones

  1. Berman reports roughly $130 in charges for the previous day and $32 so far the next morning.
  2. He notes token totals of 70 million and 25 million for the periods he describes.
  3. Without the model, rates and full context, these figures cannot establish a general cost per task.
TEXTO COMPLETO

Lee el texto editado por capítulos

Solo la transcripción
01

Watching usage and cost

Berman reviews token totals and charges and says he needs to monitor costs. The clip ends before further detail.

I'm surprised by the cost when I look at the usage display. I say I paid about $130 yesterday and have already reached $32 today, so I need to be careful about spending.

I mention 70 million tokens for the earlier period and 25 million so far today, by 9:30 in the morning. The clip ends as I start discussing costs; it does not identify the service, model or pricing, so the figures should not be generalized to every AI workload.

Más de este canal

12 diapositivas34:21EN
Matthew Berman· 27 oct 2026Matthew Berman Examines Anthropic’s IPO Filing, AI Growth and GovernanceMatthew Berman, Sam Altman · Forward FutureThe presenter reviews the S-1’s financial metrics, compute strategy and voting structure while questioning the tension between rapid AI development and safety.AnthropicAI SafetyIA empresarial+2
0:26EN
Matthew Berman· 25 oct 2026Sam Altman on Human Values and Problem-Solving in an AI WorldSam Altman · OpenAIIn a short interview excerpt, Altman considers the enjoyment of solving hard problems and the human role in interpreting results.Human-AI CollaborationFuture of WorkAI Strategy
2 diapositivas0:36EN
Matthew Berman· 25 oct 2026Kimi K3.1 and a Rubik’s Cube Solver DemonstrationMatthew Berman · Forward FutureMatthew Berman shows a scrambled virtual cube being solved and gives the Kimi K3.1 test a favorable assessment.EvaluacionesAgentes de programaciónOpen-weight models
2 diapositivas0:21EN
Matthew Berman· 24 oct 2026An AI-Generated Kimi Benchmark Chart Used Invented ScoresMatthew Berman · Forward FutureMatthew Berman asks for a graph of Kimi K3.1 Pro benchmarks, then discovers that the displayed figures are illustrative placeholders.BenchmarksEvaluacionesGenerative media
6 diapositivas25:50EN
Matthew Berman· 24 oct 2026Kimi K3.1 Pro Tested: Strong 3D Demos, Uneven Results and Competitive PricingMatthew Berman · Forward FutureMatthew Berman tests the open-weight model on coding, 3D rendering and visual explanations, then compares benchmark results and prices.Open-weight modelsBenchmarksAI cost & performance+1
2 diapositivas32:20EN
Matthew Berman· 23 oct 2026Who Is Local AI For? The Costs, Trade-offs and a Hybrid FutureMatthew Berman · Forward FutureMatthew Berman weighs data control and independence against hardware cost, setup complexity and inference speed.Local inferenceOpen-weight modelsAI cost & performance+1