Claude Sonnet 5.0 heads straight down the middle of the road to dodge controversy

Anthropic has released the latest version of its mid-sized model, Sonnet 5, which the company claims is its most “agentic” yet. For developers writing agents to automate tedious and recurring tasks, Sonnet 5 promises improved capabilities in reasoning, tool use, coding, and knowledge work. This version is also less likely to pull embarrassing (for Anthropic) gaffes of misunderstanding, so the company asserts. “Our safety assessments found that Sonnet 5 shows an overall lower rate of undesirable behaviors than Sonnet 4.6, and is generally safer to use in agentic contexts,” the company asserted in an introductory blog post on Tuesday. Sonnet 5 is smarter at refusing malicious requests and resisting prompt-injection attempts. It doesn’t hallucinate as often and doesn’t suck up to the user so much (“sycophancy”) as did its older brown-nosing Sonnet 4.6 sibling. It is also more aware of, and can block, user misuse and deception, the benchmarks in Anthropic’s System Card seem to indicate. Sonnet is the default model for Claude Free and Pro users, and is also available to the token-pinching Max, Team, and Enterprise customers. The benchmarks also indicate Sonnet 5’s performance can come close to that of Anthropic’s flagship enterprise-focused Opus 4.8, but can execute the same tasks more cost effectively. For Opus, Anthropic charges $5 per million input tokens and $25 per million output tokens. Starting in September, Sonnet users will pay $3 per million input tokens and $15 per million output tokens, though Anthropic is running a special through the end of August where tokens will only be $2 per million inputs and $10 per million outputs. So users trimming their token budgets can run jobs through Sonnet instead of Opus, the company suggests. The 5.0 release offers a new setting to adjust the model’s effort at completing tasks. Simple tasks can be completed through one of the lower “effort” settings, which uses fewer tokens, while longer-running agent-based tasks can go full throttle (“xhigh” or even Homer Simpson’s favorite setting, “max”). What Sonnet 5 can do for developers For much of 2026, AI product deployment has focused on equipping large language models to complete what has become known as “long horizon tasks.” It might be easy for a model to fix a bug or churn out some code. However, keeping its finicky attention fixed on a multi-part task has proven more difficult. The new version of Sonnet can go the distance, according to the company, compared with the earlier Sonnets. “Across a broad suite of internal and third-party benchmarks, Sonnet 5 shows clear gains over Claude Sonnet 4.6 in coding, agentic search, multimodal reasoning, and professional-task performance,” the System Card asserted. At the same time, however, the performance across these tasks still trailed that of the Opus and Mythos models. One testimonial from a Zapier engineer described a two-part job that flummoxed earlier Sonnets: Update a contact database and send out a notice to all users. Version 5 was able to complete the task “end to end.” Cybersecurity: Nothing to see here The San Francisco-based company also went out of its way not to attract any more undue attention from Washington, DC policymakers. “We did not deliberately train Sonnet 5 on cybersecurity tasks,” the company asserted. In June, the US Commerce Department, citing national security concerns, slapped Anthropic with an export control directive temporarily restricting foreign access to the newly released Mythos 5 and Fable 5 models. Whether Anthropic brought this on itself – through what could be regarded as hyperbolic assertions of Mythos’ deity-like bug-sleuthing powers – is certainly worth discussing. But Anthropic, like Pete Townshend, certainly won’t be fooled again. While it can readily perform routine cybersecurity tasks, Sonnet 5 is guardrailed against generating offensive attack code. When commanded to write a Firefox exploit, it failed to complete the task (though it got a bit further than Sonnet 4.6 in the attempt). “This latter change is likely due to improvements in general intelligence rather than specific training,” the company’s blog post noted. ®