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By Kevin Lamb
Picture two teams running the same million input tokens through the same model. One team’s tokens are cache hits, queued through the batch API. The other team’s are fresh, sent live. On a current-generation OpenAI model, cached input runs about a tenth the price of a fresh token, and batch processing cuts whatever’s left in half. Stack the two: at a list rate of $2 per million tokens, one team’s bill comes to 10 cents, the other’s to two dollars.
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By Lyne Carolyne
An LLM gateway is a proxy that sits between your applications and model providers, handling routing, failover, caching, and cost controls through one API. The strongest picks in 2026: LiteLLM for self-hosted control, OpenRouter for instant multi-model access, Portkey for managed governance, and Bifrost for production-scale throughput. Enterprises spent $37 billion on generative AI in 2025, a 3.2x jump in one year, per Menlo Ventures.
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By Djo Lopez
model-right-sizer-schema is a Claude Code skill that designs the typed contract between one agent and the controller that dispatches it. Point it at an agent plus its controller and it returns a JSON prescription with typed in/out fields, an exclusion list that keeps raw logs out of the reply, a before/after size delta, then writes the contract into the agent's own file. It picks from nine portable output-shape families, or your repo's own.
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By Kaitlin Woo
Most people rebuild the same handful of Explorer queries: the monthly close view, spend by team for the staff meeting, the filter set that isolates a service you’ve been watching for two months. When we shipped query history and favorites earlier this year, it gave you a way to save up to 12 Explorer configurations.
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By Lyne Carolyne
n8n pricing runs €24 per month for 2,500 workflow executions (Starter), €60 for 10,000 (Pro), and €800 for 40,000 (Business), with 17 percent off on annual billing and custom Enterprise pricing above that. Every plan includes unlimited users and unlimited workflows. The self-hosted Community Edition is free with unlimited executions; you pay only for your server.
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By Lyne Carolyne
CoreWeave, a GPU cloud provider, prices start at $6.16 per GPU hour for an Nvidia H100 and reaches $8.60 for a B200, sold as fixed multi-GPU nodes: an 8x H100 node lists at $49.24 per hour on demand. Spot rates run up to 60 percent below on demand, reserved contracts discount up to 60 percent, and egress is free.
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By Matthew DiLoreto
The ServiceNow integration is in Labs now, which means any CloudZero admin can switch it on and start routing cost work into their incident queue the same day. What that gives you is a full loop between the money and the work. A monthly Optimize pass surfaces recommendations with a dollar figure on each one. Pick the ones worth acting on, open incidents for all of them at once, and each ticket shows up carrying the resource, the finding, and the context an engineer needs.
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By Keith MacKenzie
Across a same-store panel of 430 CloudZero customer organizations, AI reached 2.66% of the median company's cloud bill in August 2026, up from 2.61% in July and roughly four times its level a year ago. The 75th percentile crossed 11%. The share of organizations with at least 10% of cloud spend attributed to AI jumped to 28.2% from 23.9%, the largest one-month move that tier has posted. Two-thirds of the panel now spends at least $1,000 a month on AI. The typical bill barely shifted.
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By Lyne Carolyne
GPT-6 Astra is OpenAI's flagship reasoning model, released September 3, 2026. It costs $10 per million input tokens and $50 per million output tokens on the standard API tier, with cached input at $1 and cache writes at $12.50. That is 2.5 times GPT-5.6 Sol's promotional rate and matches Anthropic's Fable 5.1 on both headline numbers. Batch and Flex halve those rates, Fast mode doubles them, and any prompt past 272K input tokens reprices the entire request.
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By Lyne Carolyne
An AI cost calculator for the whole wallet adds four lanes: seats and subscriptions, API and token usage, cloud AI services, and GPU infrastructure. Average 2026 totals run $25 per employee per month at light adoption, $100 to $150 at active adoption, and $300 or more at AI-heavy companies. Getting to your number takes four lane subtotals and three corrections.
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With CloudZero you get insights about your applications and systems, helping you manage operations at a scale that you’ve never had before. Our platform provides you with insights about every piece of your system, including the real cost of resources, resource utilization, reserved capacity and cost center efficiency.
With the accurate and trusted data provided by CloudZero you can minimize or eliminate under utilized resources, visualize costs for easy comprehension and oversee the entire software lifecycle. Nothing is out of view when using CloudZero’s Observability platform. From regional views to individual resources, you have insights at every level to help you keep your systems running smoothly.
How do we do it?
- Collect and Normalize: CloudZero’s platform starts by collecting the data from your CloudWatch, CloudTrail, VPC Flowlogs, Lambda Data Events and Billing Data from every AWS account you connect. This part of the platform is isolated in its own account for security and has read-only access to the accounts you connect.
- Populate the Stream: All of the data collected is normalized and the events, resources, statistics and billing data are organized into data streams which allow our platform to perform real-time analytics on all the data collected.
- Find Meaning: Our algorithms take in the normalized data and perform complex analytics sifting through all the data to filter noise and enhance signal. We use Machine Learning on a large scale to learn what is valuable to surface.
- Visualize Everything: The application provides opinionated visualizations of the insights determined by the platform’s AI. From regional system maps to single resources to cost of service broken down by team, CloudZero’s platform provides true observability to everyone in your organization.
Observability for Everyone. Add cost as a first-class metric and understand the financial effect of operational decisions.