Claude Opus 4.8 vs Opus 5.5: What changes when you upgrade

Give Claude Opus 4.8 and Claude Opus 5.5 the same task in a terminal, and the results look very different. On Terminal-Bench 4.0, which tests agents completing real command-line tasks from start to finish, Opus 5.5 scores 64.8%, the highest of any model in our Ready for Enterprise (RFE) LLM Benchmark. Opus 4.8 scores 23.6%.

Opus 5.5 also costs less: $4 per million input tokens and $20 per million output tokens, compared with $5 and $25 for Opus 4.8. In our overall ranking, it sits at #1, while Opus 4.8 ranks #24 and falls below our capability threshold.

That makes the decision simpler than most model comparisons, but not automatic. Below, we break down where each model wins, the one area where Opus 4.8 can still finish sooner, and what to plan for when you switch.

Opus 4.8 vs Opus 5.5: Benchmark comparison

Source: FullStack RFE LLM Benchmark, data snapshot from October 26, 2026. Rankings can change as new models ship and results are added.

Our RFE score combines six independent benchmarks with price and speed. The capability score reflects benchmark performance alone. Models below our capability threshold rank after every model that reaches it. Neither model has been tested on SWE-Bench Pro yet, so we haven't included it here.

Where each model wins

Opus 5.5 leads on five of the six benchmarks in our comparison. Opus 4.8 is barely ahead on the sixth.

Agentic tasks and coding

The Terminal-Bench results are the most important point in this comparison. Agents that write code, run commands, and fix their own errors across long sessions are where Opus 5.5 improves most, at nearly three times Opus 4.8's score. It also has the top Arena WebDev rating in our benchmark, at 1807 versus 1556 for Opus 4.8. If your use case involves complex tasks with many tool calls, move it first.

Factual accuracy and research

Opus 5.5 scores 72.2% on SimpleQA Verified, compared with 53.0% for Opus 4.8. That improvement is valuable for research, document review, and reports, where fewer factual errors means less checking afterward.

Math and human preference

Opus 5.5 also leads on FrontierMath Tiers 1–3 (91.2% vs. 80.0%) and on Arena Text, a blind human-preference rating of written responses (1509 vs. 1481).

Where Opus 4.8 holds its own

Opus 4.8 scores slightly higher on GPQA Diamond, which tests graduate-level science, at 91.0% versus 90.6%. The difference is too small to drive a decision.

Is Opus 5.5 cheaper than Opus 4.8?

Yes. Input pricing drops from $5 to $4 per million tokens, and output pricing drops from $25 to $20. That's 20% less on both sides, or $8.00 versus $10.00 per million tokens using our 3:1 input-to-output blend. Anthropic released Opus 5.5 on September 22, 2026. Opus 5 had the same $5 / $25 pricing as Opus 4.8, so Opus 5.5 is the first Opus model to lower it.

Your actual usage may not fall by exactly 20%, though. Opus 5.5 always thinks before it answers, and thinking is billed as output tokens. Some tasks may use more output tokens than they did on Opus 4.8, while others may need fewer retries. Compare cost per completed task, not just the price per token.

Which model finishes sooner?

It depends on response length. Opus 5.5 streams output slightly faster in our measurements, at 81 tokens per second versus 74. Opus 4.8 returned its first token sooner in our snapshot, at 1.24 seconds versus 3.42 seconds.

The first-token figure needs some care. It's measured over a short window, so it varies more than output speed, and for a model that always reasons, it may include thinking time. Here's the estimated completion time for each model:

Estimates use time to first token plus output length divided by measured output speed. Real response times also depend on effort settings, tool calls, and load.

On these numbers, Opus 4.8 finishes short answers a couple of seconds sooner, and the two models are close on longer ones. For background agents, that difference rarely matters. For short, user-facing replies, test both on real prompts before you switch.

Do you have to switch now?

No. As of the time of writing, Anthropic's model deprecations page lists Opus 4.8 as active, with retirement not sooner than May 28, 2027. Anthropic gives at least 60 days' notice before retiring a public model.

Older Opus models are already gone: Opus 4 and Opus 4.1 were retired in mid-2026. Since Opus 5.5 is both better and cheaper, there's little reason to wait for a deadline. Plan the switch as a project, on your own schedule.

How to plan the switch from Opus 4.8

Changing the model name in your setup is the easy part. Both Claude Opus models use the same API, but a few details work differently on Opus 5.5: 

• Thinking is always on. On Opus 4.8, thinking is off unless you request it. On Opus 5.5, it runs on every request and can’t be disabled. Use the effort setting to control how much the model thinks, then retest latency and output token usage.
• Forced tool use returns an error. If your code forces the model to call a specific tool, update it so the model can choose.
• Sampling parameters are gone. Opus 5.5 returns an error if a request includes temperature, top_p, or top_k. Remove them and guide behavior through prompting.
• The computer-use tool has a new version. On the Claude API and Google Cloud, Opus 5.5 rejects the older computer-use tool and requires the current toolset. On Amazon Bedrock, the older version still works.
• The default effort level is lower. Opus 4.8 defaults to high effort, and Opus 5.5 defaults to medium. Set effort explicitly, and test a few levels on your own evaluations rather than carrying over Opus 4.8’s settings.
• Priority Tier isn’t available. If you rely on Priority Tier for Opus 4.8, check your capacity plans before switching.

Then test. Build a small evaluation set from real workflows and run the two models on the same prompts and tools. Compare completion rate, errors, latency, and cost per accepted result. Expect to rewrite some prompts, especially ones written to work around Opus 4.8's limits. Keep the model choice in configuration so you can roll back quickly if a workflow gets worse.

You don't have to pick one model for everything, either. Different things suit different models, so the right model for a short, latency-sensitive reply may not be the right model for a long agent run.

^{If you're on Opus 5 instead, read Claude Opus 5.5 vs Opus 5: Enterprise guide for coding, knowledge work, and cost.}

How FullStack can help

FullStack is proud to say we’re Anthropic Certified. Our forward-deployed engineers embed with your team, test new Claude models against your real workloads, update the prompts and integrations that need to change, and move each workflow over without disrupting production.

^{Compare these models in the RFE benchmark.}