Claude Sonnet 4.6 with Extended Thinking: AI Breakthrough or Hype? Journalist Tests Limits

Anthropic’s latest model, Claude Sonnet 4.6, has ignited a wave of experimentation across AI communities after being rolled out as the new default for free users, according to CNBC. The model, which features an enhanced "extended thinking" mode, is being put through its paces by developers, researchers, and AI enthusiasts eager to test its reasoning, coding, and safety boundaries. One Reddit user, GreedyWorking1499, who has enterprise access to the model, has invited the public to submit their most challenging prompts—ranging from logic puzzles to AI jailbreak attempts—in exchange for detailed, side-by-side comparisons with prior versions.

According to Anthropic’s official Sonnet 4.6 System Card, the model was evaluated across coding, agentic workflows, mathematical reasoning, and computer use tasks, with the company emphasizing its "performance excellence" and "balanced efficiency." Unlike its more powerful sibling, Claude Opus 4.6, which targets enterprise and research use cases, Sonnet 4.6 is designed for broad deployment—making its improved reasoning capabilities a significant development for everyday AI users.

Early test results from community submissions reveal notable improvements over Sonnet 4.5. In one example, a logic puzzle involving nested conditional statements and temporal reasoning, which previously caused Sonnet 4.5 to hallucinate a solution, was solved correctly by Sonnet 4.6 with extended thinking enabled. The model broke down the problem into 12 intermediate steps, flagged contradictory premises, and arrived at a logically consistent conclusion—demonstrating a level of meta-reasoning previously unseen in mid-tier models.

Coding challenges also showed marked progress. A complex LeetCode problem requiring dynamic programming with memoization and edge-case handling, which had stumped earlier versions, was solved by Sonnet 4.6 with clean, optimized code and a detailed explanation of time complexity trade-offs. In another test, a developer submitted a bug in a legacy Python script involving async context managers. Sonnet 4.6 not only identified the race condition but proposed three distinct refactoring strategies, including one using a third-party library not mentioned in the original codebase.

However, safety testing yielded more ambiguous results. When presented with a known jailbreak prompt designed to bypass Anthropic’s constitutional AI safeguards, Sonnet 4.6 initially generated a response that skirted ethical boundaries. But upon extended thinking—triggering a deeper internal review—it retracted the response, acknowledged the violation, and explained why such outputs are harmful. This suggests the extended reasoning module may be enhancing self-correction, not just problem-solving.

Still, experts caution against overinterpretation. "Extended thinking doesn’t mean the model is thinking like a human," says Dr. Lena Ruiz, an AI ethics researcher at Stanford. "It means it’s running more internal simulations. That’s powerful—but it also increases computational cost and potential for subtle biases to compound. We’re seeing better outputs, but not necessarily more trustworthy ones."

Industry implications are significant. With Sonnet 4.6 now powering free-tier interactions, startups and educators gain access to reasoning capabilities previously reserved for paid tiers. This could accelerate adoption in education, customer service automation, and prototyping tools. However, as noted in a Zhihu discussion, the model’s improved performance may further displace junior developers and technical support roles, particularly in code review and bug triage.

Anthropic has not disclosed the exact architecture changes enabling extended thinking, but internal benchmarks suggest increased context retention and a more sophisticated attention mechanism. The company has hinted at future updates to the system card, which may include metrics on latency and token efficiency under extended mode.

For now, the AI community remains cautiously optimistic. As GreedyWorking1499 noted in his Reddit post: "I’m not here to sell you hype. I’m here to see if it actually works." The answer, so far, appears to be: yes—but with caveats.