What a task costs on Opus 5.5

來源原標題

What a task costs on Opus 5.5

機構

Anthropic

原始標籤

Claude Code

原始連結

https://claude.com/blog/what-a-task-costs-on-opus-5-5

摘要原文

What a task costs on Opus 5.5 Opus 5.5 costs less per token than Opus 5. Category Claude Code Product Claude Code Date September 22, 2026 Reading time 5 min Share Copy link https://claude.com/blog/what-a-task-costs-on-opus-5-5 Author(s) Addy Osmani The cost of a task, and the cost of a retry You don't set out to buy millions of tokens. You set out to build a feature, finish a migration, or run a task. The token count is whatever the model needed to get there. Two models with the same cost per token can cost very different amounts on the same task. One reads the code once. The other reads it, tries a fix, and reads it again. Each of those steps is a turn, and each turn resends the conversation so far. So the model that needs more turns costs more, even at the same price. By the end of this post you should be able to answer three questions about your own work: What do my typical tasks cost me on Opus 5.5? Which settings change that, and by how much? How do I check my own session usage? The tradeoff I want to share upfront is that every way to spend fewer tokens can also cost you a finished task. Lower effort, a smaller model, or less context can all certainly save tokens. A retry costs more than those savings. This post attempts to put a price on each tradeoff. Some numbers here are list prices, and some are illustrations built from them. The figures are interactive, so change the inputs as you read. These are best effort illustrations, so be sure to check our docs and your own math. What does a task cost? A task in Claude Code is a loop. The model reads the conversation, calls a tool, reads the result, and goes round again until it's done. Each trip round the loop is one request. Four things set what the loop costs. Turns. Every turn resends the conversation so far. Fewer turns means less input processed. Cache reads. Most of what a turn resends is text the model saw on the previous turn. It's billed as a cache read, at a small fraction of the input price. Output token type. The most expensive tokens, at five times the input price. Thinking is billed as output, so a model that reasons less on the way to the answer costs less. Model. Each model has its own prices, listed on the pricing page, so the model you pick sets the price of every token. Our examples use Opus 5.5 API list prices: $4 per million input tokens, $20 per million output tokens and $0.20 per million cache reads. Like the calculator further down, the examples bill cached input at the read price and everything else at the input price, and leave out cache writes. The token counts are illustrations. Turns Let’s say a task starts with 20K tokens of context and grows to 120K as the model reads files and tool results. At 40 turns, the average turn sends about 70K tokens. That's about 2.8M input tokens for the task, though the conversation never grew past 120K. With 90% read from cache, the input costs about $1.62. The same task in 25 turns processes about 1.75M tokens and costs about $1.02 in input. A turn costs more than the tokens it adds, because it resends everything before it. So the cheapest turn is the one you don't need. One habit that can cut turns is giving the model a way to check its work. For example, a test to run, a build, or a script that calls the endpoint. A model that can check its own work finds its mistakes earlier. A model that gathers what it needs in one pass, and batches its tool calls, pays the resend fewer times too. Cache reads The same 2.8M input tokens cost $11.20 if none come from cache. At a 90% hit rate they cost $1.62, and at 96% about $0.99. No other setting moves input cost this much. A steady session keeps a high hit rate on its own. I cover some actions to avoid breaking your cache later in this post. Output tokens On Opus 5.5, an output token costs 100 times a cache read. The 60K output tokens of a typical task cost $1.20, the same as reading 6M tokens from cache. Output includes thinking. You pay for all of it, even when Claude Code only shows you a summary. That's why effort, which mostly changes how much the model thinks, moves the bill so much. Model A model with cheaper cache reads mostly helps long sessions. One with cheaper output mostly helps tasks that need a lot of reasoning. What changed in Opus 5.5 Two things changed: the price, and how much work the model does. Every price line is lower. Input and output tokens are 20% cheaper than on Opus 5. Cache reads are 60% cheaper. The input price falls, and the read rate falls with it, from a tenth of the input price to a twentieth. Fig A compares the two models per million tokens. These are API list prices. On a Pro, Max or Team plan, the lower Opus 5.5 price is passed on to your limits, including cached context, so they go about 25% further than on Opus 5. The extra cut on cache reads is an API price change. Fig A. Price per million tokens. On an API key, the cache-read price cut matters most for Claude Code. A long agentic session spends most of its input on cache reads. In the session priced in Fig B below, the cache line falls from $1.00 to $0.40, the largest drop on the receipt. How much you save depends on the shape of your work. A session that is mostly cache reads can save up to 60% on input. A short question with no cache and a long answer can save up to 20%, because output dominates it. Most Claude Code tasks sit between the two. The calculator below shows where yours sits. Opus 5.5 can use more tokens on an answer, because it always thinks before it replies. We expect people to get more done on Opus 5.5, but it varies by task, so measure it on your own work. Fig C compares cost per task on the two models. This part depends on your work far more than the price does. On a well-scoped task, both models finish in about the same number of turns, and the price cut is all you get. The gap should be biggest on open-ended tasks, where a model can spend many turns on the wrong idea. No single number holds for every codebase, so measure it (see the last section). Long runs end with a report. Opus 5.5 closes a long run with what it changed, what it found, and what it needs from you. That can save money too, because you rerun a session less often when you can see what happened. The same tasks side-by-side Fig B prices one session on both models with the same token counts. So the difference is the price change and nothing else. Switch models to compare. The token counts are illustrative. Same task on Opus 5 On Opus 5.5 $3.50 at Opus 5 list prices Fig B. Illustrative session with the same tokens on both models, so this is the price change alone. Fig B. Illustrative session with the same tokens on both models, so this is the price change alone. The receipt has the three lines /usage shows for a session. Cache reads are the biggest line by tokens, at 2M. Output is the smallest by tokens and the biggest by cost. Fresh input sits between them. It covers the first read of each file and each new tool result. Fig B gives both models the same token counts, so it shows the price change alone. Your own sessions can use more or fewer tokens on Opus 5.5. Priced that way, the session costs about 31% less. A recorded run adds the second effect, the change in how much work the model does. On a task with a false start, the gap should widen. Try your own numbers Set what one of your tasks uses, or start from a preset. The presets are pretty illustrative but I’d still recommend doing your own math. Cached input bills at the cache-read price and fresh input at the input price, so the cache slider shows how much of the gap comes from cache reads. To fill the sliders from a real session, run /usage at the end of a task. The Session block gives input, output and cache figures. The last slider is your assumption about how much less work Opus 5.5 does on your tasks. Leave it at 0% for the price change alone. To set it from your own work, here's how: run the same task on Opus 5 and on Opus 5.