Introducing Claude Sonnet 5.5 \ Anthropic

Introducing Claude Sonnet 5.5, the second model in the Claude 5.5 family. It’s a clear upgrade over Claude Sonnet 5, runs 30%+ faster, and costs up to 30% less for most work.
Sonnet 5.5 is a faster, lower-cost complement to Claude Opus 5.5. Where Opus 5.5 is built for complex work requiring careful judgment, Sonnet 5.5 is strongest at well-scoped everyday tasks, fixing bugs, and creating polished documents, slides, and spreadsheets. It’s also got a sharp eye for design. Claude Haiku 5.5, built for high-volume and cost-sensitive applications, will join the Claude 5.5 family in the coming weeks.
Sonnet 5.5 improves over Sonnet 5 on:
Performance. Sonnet 5.5 scores 70.6% on Terminal-Bench 4.0, an agentic coding evaluation, compared to Sonnet 5’s 10.3%. It scores two points below Opus 5.5 on GDPval-AA, a test of real-world work across a variety of occupations. And it’s strong on long-horizon work and image understanding—it’s the first Sonnet model to beat Pokémon Red working only from screenshots.
Collaboration. Like Opus 5.5, Sonnet 5.5 writes more clearly than our previous generation of models; early testers described it as a better partner for collaboration than Sonnet 5. Its speed also makes it well suited to fast iteration on less complex tasks.
Cost. Sonnet 5.5 is priced the same as Sonnet 5 at $2 per million input tokens and $10 per million output tokens, but it typically needs far fewer tokens to do the same work. Cache reads cost $0.10 per million tokens, half of Sonnet 5's $0.20. In our testing, it costs up to 30% less per task than its predecessor.
Speed. Sonnet 5.5 generates outputs 30%+ faster than Sonnet 5, making it our fastest Sonnet model to date.
Alignment and safety. On our automated behavioral audit, Sonnet 5.5 improves on or matches Sonnet 5 on most measures of alignment. Because its cybersecurity capabilities are comparable to Opus 5’s, it’s the first Sonnet model to launch with cyber safeguards and fallbacks like those we’ve developed for our most capable models. Its biology safeguards are the same as Sonnet 5’s. Both safeguards target a narrow set of high-risk requests; routine software development and most life sciences work are unaffected.
Sonnet 5.5 improves on Sonnet 5 across domains—in some cases dramatically. On several evaluations, Sonnet 5.5 at Max effort even performs comparably to Opus 5.5. However, benchmark scores capture only one facet of a model’s capabilities; in our own testing, and in that of external testers, Opus 5.5 remains clearly stronger at complex, open-ended work requiring sustained judgment.
For details on how we run our evaluations, see the Sonnet 5.5 System Card.
The charts below plot each model’s score against its cost per task at every effort level. As effort goes up, models typically work for longer, leading to a higher cost per task but generally also a higher score. The closer a point is to the top left of the chart, the more capability it delivers per dollar.
On several benchmarks, Sonnet 5.5 at Low or Medium effort beats Sonnet 5’s best score for about a tenth of the cost per task. It complements Opus 5.5 best when running at lower effort settings, where it costs less per task. At higher settings, it can perform comparably at a similar cost.
Terminal-Bench 4.0 measures how well a model can complete complex, multi-step professional tasks within a command-line interface. At Medium effort, the default in the Claude apps, Sonnet 5.5 far exceeds Sonnet 5’s best score for less than a tenth of the cost per task.
Terminal-Bench and OpenAI did not report GPT-6 Sol performance publicly, so we report GPT-5.6 Sol here.
FrontierCode measures whether an agent’s code changes would be merged. At High effort, the default on the Claude Platform, Sonnet 5.5 matches GPT-6 Sol’s best score for about a fifth of the cost per task.²
CursorBench evaluates coding agents on ambiguous, multi-file tasks taken from real Cursor sessions. Sonnet 5.5 at Low effort exceeds Sonnet 5’s best score for less than a tenth of the cost per task.
CursorBench 4.0 does not report GPT-6 Sol performance publicly, so we report GPT-5.6 Sol here.
On AA-Briefcase, a new benchmark of long-horizon knowledge work, Sonnet 5.5 at Medium effort bests Sonnet 5’s best score for about one ninth of the cost per task.³
Sonnet 5.5’s jump in performance is particularly noticeable in coding. At High effort on FrontierCode, it scores 10 points higher than Sonnet 5 at the same setting, at about one fifteenth of the cost per task. On CursorBench, which tests models on tasks from real Cursor coding sessions, its best score is within about two points of Opus 5.5.
Early testers appreciated how quickly Sonnet 5.5 can understand a codebase. They were also struck by its efficiency: in head-to-head runs, it batched tool calls together more than Sonnet 5, leading to fewer steps and lower costs.
“In Epic’s early testing, Claude Sonnet 5.5 cleared the same quality bar you’d expect from a higher-tier model, holding up on a system design audit and a data flow review. The new model managed tens of thousands of lines of code for gameplay system architecture, kept responses snappy, handled multi-hour tasks, and delivered with less prescriptive prompting.”
“Claude Sonnet 5.5 cooks. Fast at coding and can be steered quickly in iterative workflows. But it can still work long if it needs to. It’s got some of Opus 5.5’s natural writing upgrades, which makes it more fun to work with.”
“Claude Sonnet 5.5 shows better judgment than Sonnet 5 across different levels of complexity, while spending significantly fewer output tokens. Sonnet 5’s tendency to reach for web search too often and its high token use are both gone in this new model. We plan to move simple and moderate reviews over now, and more in the coming weeks.”
“Claude Sonnet 5.5 delivers frontier-level performance on CursorBench 4.0 at 55.5%, second only to Opus 5.5. We think it will be a hit with developers looking to balance performance with cost.”
“Across 118 re