**Short answer:** Claude Opus 5.5 is Anthropic's newest top-tier AI model, announced in September 2026 as the first model in its Claude 5.5 family. Anthropic prices it at $4 per million input tokens and $20 per million output tokens, 20% below Opus 5, and says it costs about 40% less to run than Opus 5 on typical workloads while generating output more than 30% faster. Anthropic also says it writes clearer answers and stays inside the limits it is given more reliably. Most small business owners will meet this model inside other software, not by using it directly, so the practical question is how to judge a tool that says it runs on the newest model. The short version: test any new model on ten of your own tasks before you switch or pay more for it.

Every few weeks a new model arrives with a benchmark table and a headline number. This guide follows the order of Anthropic's announcement: performance and cost, coding, security, knowledge work, communication, safety, and availability. It then adds what the announcement can't tell a business owner, namely which claims come from the vendor, which come from outside testers, and how to run a fair test yourself. Velora Media did not run any of the benchmarks below, and each figure is attributed to its source.

## Key takeaways

- Opus 5.5 costs $4 per million input tokens and $20 per million output tokens, down from $5 and $25 for Opus 5.
- Anthropic's own caveat is that benchmark margins have become a less reliable guide to real-world differences between top models.
- It does not win every test: GPT-6 Astra scores higher on two benchmarks in Anthropic's own table.
- Better resistance to prompt injection matters most if an AI reads customer messages and can act on them.
- A ten-task test on your own work tells you more than any leaderboard.

## What is Claude Opus 5.5?

Claude Opus 5.5 is a large language model from Anthropic, the company that makes the Claude assistant. Anthropic says it performs at the level of its higher-priced model, Claude Fable 5.1, on most work, and that it is a major step up from Opus 5. It is available through Anthropic's own platform and through Amazon Web Services, Google Cloud, and Microsoft Azure, and developers call it by the name claude-opus-5-5. At launch, Anthropic also said Claude Sonnet 5.5 and Claude Haiku 5.5 would follow in the coming weeks.

## Performance and cost

Anthropic lists the price at $4 per million input tokens and $20 per million output tokens. Cache reads, which make up most of the cost of long agent sessions, are $0.20 per million tokens, 60% below Opus 5. Anthropic also raised five-hour usage limits on its Pro, Max, Team, and seat-based Enterprise plans. VentureBeat and Finout report the same per-token figures, and Finout also lists a batch rate of $2 and $10.

Here is a selection of the benchmark results Anthropic published, using the figures from its announcement:

| Benchmark | Opus 5.5 | Fable 5.1 | Opus 5 | GPT-6 Astra |
|---|---|---|---|---|
| Terminal-Bench 4.0 (agentic coding) | 66.4% | 55.8% | 52.3% | 57.9% |
| GDPval-AA v2.1 (work across 44 occupations, Elo) | 1846 | 1735 | 1708 | 1542 |
| AutomationBench (business workflows) | 40.0% | 31.4% | 26.9% | 41.4% |
| Terminal-Bench-Science 0.1 (agentic research) | 58.7% | 52.6% | 29.0% | 64.6% |

A few cautions go with that table. First, Anthropic itself writes that at these capability levels benchmark margins are a less reliable guide to real-world differences, and that in its own use the gap between Opus 5.5 and Fable 5.1 is narrower than the scores suggest. Second, Opus 5.5 does not lead everywhere. GPT-6 Astra scores higher on AutomationBench, and on the agentic research benchmark Astra scores 64.6% against Opus 5.5's 58.7%. Third, the GPT-6 Astra figures are as reported by OpenAI, and VentureBeat noted that there is no clean public same-setup comparison with OpenAI's models on the major agentic benchmarks and that the customer results Anthropic published were vendor-selected. Read the table as a rough guide.

### What a million tokens means for a small business

A token is a small chunk of text, and a rough rule of thumb is that one token equals about three quarters of a word. As an illustration only, imagine asking a model to summarize 1,000 customer emails of about 250 words each into 60-word summaries. That is roughly 333,000 input tokens and 80,000 output tokens, which at Opus 5.5's list price comes to about $3. Real bills run higher, because the model's reasoning also counts toward usage (Anthropic says Opus 5.5 can no longer be run with thinking switched off), and tools that act on their own use many more tokens than a single summary. Even so, for ordinary text work the model's own fee is rarely the biggest cost. Setup, integration, and the time you spend checking the output usually are.

## Coding

Anthropic says Opus 5.5 is especially good at long jobs such as codebase-wide migrations and audits. In one early tester's run, it audited and fixed a 200,000-line codebase in under three hours, where Opus 5 took more than 20 hours and used 2.5 times as many tokens. In an internal test, it translated the HAProxy load-balancing software from C to Rust in 9.5 hours against 12 for Fable 5.1, at 51% less cost, and both rewrites passed nearly all of HAProxy's own regression tests. On Terminal-Bench 4.0, Anthropic says it matches GPT-6 Astra's score at about 40% of the cost per task, though that comparison is Anthropic's own.

You will probably never run a codebase migration. But this is the work behind website builders, booking tools, and automations, so faster and cheaper coding agents may eventually lower what builders charge to create and maintain custom features. That depends on whether vendors pass the savings along, so treat it as a possibility.

## Security and prompt injection

Prompt injection is when hidden instructions in an email, web page, or review try to hijack an AI that reads it, such as a line telling the assistant to ignore its rules and send out customer data. Anthropic says Opus 5.5 matches or beats Opus 5 against prompt injection in every setting it tested, and that it ties Fable 5.1 for the lowest injection success rate of any model on a benchmark run by the security firm Gray Swan. Anthropic also says a classifier screens every action before it runs and that its sandbox for agents is open source.

"Matches or beats" does not mean immune. If a tool reads your customers' messages and can send texts, issue refunds, or edit your calendar, the practical safeguard is to limit what it can do without a person's approval, whichever model sits underneath.

## Knowledge work

In one Anthropic test, models wrote a report on a company's quarterly performance using only information they could find on a copy of the web where the earnings release was hard to locate, and an automated grader checked every figure and quote against sources. Opus 5.5 produced 16 of 18 reports that cleared the bar of containing no invented figure or quote, which means 2 did not. Anthropic says neither Fable 5.1 nor Opus 5 cleared the bar in any attempt. In a separate test of a fictional merger between two HR software companies, Opus 5.5 built the financial model and presentation in 63 minutes against 93 for Opus 5, at half the cost.

Research summaries, competitor write-ups, and proposals are the kind of work small businesses actually hand to AI. The lesson from Anthropic's own numbers is that a strong result still leaves room for an occasional invented figure, so check any number before it goes to a customer.

## Communication

Anthropic says Opus 5.5 puts the most important information first, uses less jargon, and follows the writing rules you give it, and it calls this one of the most common areas of feedback on Opus 5. A tester at the payments company Ramp said a design spec came back usable with very minimal edits. If true in your own use, shorter and clearer answers mean less time reviewing them. Write your style rules down once, such as plain language, no jargon, and short sentences, and test whether the model follows them.

## Safety

Anthropic reports that on its automated behavioral audit, which runs across nearly 2,000 scenarios, Opus 5.5 scored better than any recent Claude model on nearly every measure of misaligned behavior. In a new test of whether a model tries to cross containment boundaries, it did so about 85% less often than Opus 5 or Claude Mythos 5.1, and every attempt was low severity and self-reported. Anthropic also lists limits: it calls building tests that catch every failure before release an unsolved problem, and it sees signs that Opus 5.5 often suspects it is being evaluated.

Two safeguards affect real use. Most cybersecurity tasks are routed to an older model, Opus 4.8, and some biology research requires applying to a verification program. For a typical small business neither will matter. For the wider debate about AI autonomy, and why the AI answering your phone is a different kind of system, see [Anthropic's AI risk warning and what it means for small business](/blog/anthropic-ai-risk-warning-what-it-means-for-small-business).

## Availability

Opus 5.5 is available on Anthropic's platform, Amazon Web Services, Google Cloud, and Microsoft Azure. Anthropic says it is available with zero data retention, the way earlier Opus models were, which matters if you handle customer information, though whether a given tool uses that option is up to the vendor. Many owners will first see Opus 5.5 as a model option inside other products, and Anthropic's announcement quotes early testers including GitHub, Ramp, Stripe, and Deloitte.

## How to test a new AI model on your own work

No leaderboard measures your tasks. This five-step test takes an afternoon:

1. Write down ten real tasks, such as replying to a review, summarizing a week of calls, drafting a quote follow-up, or explaining a price change.
2. Run the same ten through your current tool and the new one, and have someone who does not know which is which pick the better answer for each.
3. Count the cost per task, including the time you spend editing, not the price per million tokens.
4. Check what each tool can do without asking. Start with drafts that a person approves before anything is sent, charged, or deleted.
5. Ask the vendor which model and settings they use, where your data is stored, and whether it is retained.

Switch when your own test shows fewer edits or lower cost. A headline saying a model improved isn't reason enough. For how rapidly AI is advancing in other areas, see [GPT Astra and how fast AI is advancing](/blog/gpt-astra-3d-modeling-how-fast-ai-is-advancing), and for the open-model side of the same race, see [K2 Horizon explained](/blog/k2-horizon-open-ai-models-reasoning-training-explained).

## Where Velora fits

The model is only part of what you get from an AI assistant. How well it knows your business matters too, and generic prompts produce generic work. Velora Media's [AI Prompt & Workflow Pack](/shop/ai-prompt-workflow-pack) starts at $250 and delivers 15 to 25 custom prompts and mini-workflows built around how your business operates, as a Notion workspace and PDF, so you start from your own voice and processes instead of a blank box. Those prompts also make a good starting set for the ten-task test above.

## Frequently asked questions

### What is Claude Opus 5.5?

Claude Opus 5.5 is Anthropic's newest top-tier AI model and the first in its Claude 5.5 family, announced in September 2026. Anthropic says it matches its higher-priced Claude Fable 5.1 on most work at lower cost.

### How much does Claude Opus 5.5 cost?

Anthropic lists $4 per million input tokens and $20 per million output tokens, 20% less than Opus 5, with cache reads at $0.20 per million tokens. Anthropic says it costs about 40% less than Opus 5 on typical workloads.

### Is Claude Opus 5.5 better than GPT-6 Astra?

It depends on the test. In Anthropic's table, Opus 5.5 scores higher on Terminal-Bench 4.0 (66.4% against 57.9%) and GDPval-AA, while GPT-6 Astra is slightly ahead on AutomationBench (41.4% against 40.0%). The Astra figures are as reported by OpenAI, and no independent same-setup comparison exists yet.

### How is Opus 5.5 different from Opus 5?

Anthropic says it costs less, runs more than 30% faster, writes shorter and clearer answers, resists prompt injection better, and attempts to cross containment boundaries about 85% less often.

### Do small businesses need Claude Opus 5.5?

Not directly. Most will encounter it inside other software. The better question is whether a tool that uses a newer model gives you fewer edits or lower costs on your own tasks.

### Is Claude Opus 5.5 safe for customer data?

Anthropic says Opus 5.5 is available with zero data retention. Whether a particular product enables that option is the vendor's choice, so ask where your data is stored and whether it is kept.

### Where can I use Claude Opus 5.5?

Through Anthropic's own platform, Amazon Web Services, Google Cloud, and Microsoft Azure, and in products built on those. Developers use the model name claude-opus-5-5.

## Related reading

For a plain-language look at what small business owners should understand about AI right now, see [what small business owners need to understand about AI now](/blog/what-small-business-owners-need-to-understand-about-ai-now). For the cost of AI-produced video, see [AI commercial cost for small business](/blog/ai-commercial-cost-for-small-business).

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## Sources

- Anthropic, "Introducing Claude Opus 5.5." [anthropic.com](https://www.anthropic.com/claude-opus-5-5)
- VentureBeat, "Anthropic releases Claude Opus 5.5, beating Fable 5.1 on key agentic benchmarks at 60% cheaper API price," September 22, 2026. [venturebeat.com](https://venturebeat.com/technology/anthropic-releases-claude-opus-5-5-beating-fable-5-1-on-key-agentic-benchmarks-at-60-cheaper-api-price)
- Finout, "Claude Opus 5.5 Pricing 2026: What Anthropic's New Flagship Actually Costs," September 23, 2026. [finout.io](https://www.finout.io/blog/claude-opus-5.5-pricing-2026-what-anthropics-new-flagship-actually-costs)