Claude Opus 4.6

Claude Opus 4.6 bestanden · 3 sentences

When reasoning is enabled, the model generates extensive internal chain-of-thought tokens that are produced—and billed—before the user-visible answer even begins, often multiplying total token consumption by 5–10× per request. Because our pricing is strictly per-token for both input and output, those hidden "thinking" tokens hit the invoice just as hard as the final response, even though end users never see them. To bring costs back in line, we can tune the reasoning effort parameter, cache common prompts, and route only genuinely complex queries to the reasoning model while handling routine tasks with a lighter, cheaper one.

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Claude Opus 4.6 bestanden · 8/8 cases

```python def longest_run(xs): if not xs: return 0 best = 1 cur = 1 for i in range(1, len(xs)): if xs[i] == xs[i - 1]: cur += 1 best = max(best, cur) else: cur = 1 return best ``` The original code had two related bugs stemming from the fact that it counted additional consecutive elements (starting from 0) rather than the total length of a run (starting from 1): first, `best` and `cur` were initialized to 0 instead of 1, which meant a single-element list (where the loop never executes) returned 0 instead of the correct answer 1; second, when a mismatch was found, `cur` was reset to 0 instead of 1 (failing to count the current element as the start of a new run), which meant that if the longest run occurred at the very end of the list, the comparison `best = max(best, cur)` on the next matching step would be w […]

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Claude Opus 4.6 bestanden · 5/5 fields, guidance "withheld pending the Q4 close"

```json { "company": "Meridian Robotics", "quarter": "September quarter", "revenue_usd_m": 412, "growth_pct": 11, "guidance": "withheld pending the Q4 close" } ```

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Claude Opus 4.6 bestanden · 118 words, 0 banned, 1 question

**Introducing Cross-Provider Prompt Caching** Why pay for the same computation twice? Our new API gateway feature intelligently caches prompt responses across multiple LLM providers, reducing latency by up to 60% and cutting costs significantly for repeated or similar queries. When your application sends a prompt that matches a cached response—regardless of whether it originally came from OpenAI, Anthropic, or Cohere—the gateway serves the stored result instantly. You maintain full control over cache duration, invalidation rules, and provider-specific overrides through a simple configuration dashboard. The feature supports both exact and semantic matching, letting teams optimize for speed or flexibility based on their use case. Available today on all Pro and Enterprise plans with no additional setup required.

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