Cloudflare Workers AI now runs Kimi K2.5
Cloudflare's large-model Workers AI post is useful because it connects model choice, inference cost, and agent infrastructure in one practical story.
Source
Powering the agents: Workers AI now runs large models, starting with Kimi K2.5
Why I saved it
This is the kind of Cloudflare post I like because it is not only a launch note. It explains why large open models matter for real agent systems.
The interesting part for me is the cost story. Cloudflare describes using Kimi K2.5 inside internal development workflows and automated code review. That makes the article more grounded than a normal model announcement.
My notes
- Kimi K2.5 is positioned as a frontier open model for agentic tasks.
- Cloudflare talks about a 256k context window, tool calling, vision inputs, and structured outputs.
- The post connects model serving with Durable Objects, Workflows, Dynamic Workers, Sandbox, and Agents SDK.
- The strongest takeaway is that model quality is only one layer. Serving, observability, and workflow infrastructure decide whether agents are practical.
What I want to remember
If I build agents on a cloud platform, I should compare the whole stack, not just model benchmarks. A cheaper model with good routing, logs, and stable execution can be more useful than a stronger model that is painful to operate.