Same price, cheaper fast mode: Opus 4.8 argues on unit economics

Sort the cost levers in this release by how enforceable they are. The price hold and the fast mode discount are line items a forecast can carry: Anthropic says Opus 4.8 arrives at the same price as 4.7 ^[1], and that fast mode, running at 2.5 times speed, now costs a third of what it did on previous models ^[2], a 67 percent cut on that line ^[10]. Token efficiency is the third lever and it is not a price at all. It is a claim about how many steps a given job takes. A tester quoted in the announcement says tool calling on CursorBench uses fewer steps for the same intelligence ^[3], and Databricks says its Genie agent reads PDFs and diagrams at 61 percent cheaper token cost than on Opus 4.7 ^[6], which works out to roughly 2.6 times the work per dollar on that workload ^[14]. Nothing in the announcement says any other workload resembles Genie's.

The effort control matters more than a setting usually would, because the same CursorBench tester reports gains at every effort level ^[3]. If the low setting improved too, then the cheap tier stops being the one you avoid for real work, and the dial becomes a way to buy accuracy per job instead of per contract. High effort on the migration and low effort on the lint pass, with a month-end invoice that reflects choices somebody made and can defend.

Dynamic workflows in Claude Code is aimed at very large-scale problems ^[11], which is where per-step efficiency compounds and where the effort setting stops being a matter of taste. It is also where the reliability ceiling becomes visible. On the Legal Agent Benchmark described in the announcement, 4.8 posts the highest score recorded and is the first model to break 10 percent on the all-pass standard ^[12]; a shade over one case in ten clears every check, and the rest fail at least one ^[13]. That is a genuine gain on a hard test, and it is also the number that governs how much work runs without a human reading the output.

Anthropic's own summary is that early testers found the model more reliable and sharper in its judgment on agentic tasks ^[8]. Judgment is not a budget line. The three numbers above are, and they are the part of this release a finance team can hold an engineering org to.