Claude Opus 5.5 cuts API costs and response times, but reasoning gains remain unproven

Editorial illustration of a transparent AI reasoning engine balancing efficiency against an unfinished maze, representing faster and cheaper inference without better reasoning.

Anthropic’s Claude Opus 5.5 is cheaper and faster to run than Opus 5, but a small set of reasoning tests found no clear capability improvement. In The New Stack’s comparison, both models solved two problems and failed a difficult ordering task, while Opus 5.5 sometimes used substantially fewer output tokens.

Lower API pricing

Anthropic lists Opus 5.5 at $4 per million input tokens and $20 per million output tokens, compared with $5 and $25 for Opus 5. The source estimates that the direct price reduction accounts for a 20% saving; the larger reduction claimed by Anthropic depends on the newer model generating fewer tokens. Anthropic also claims Opus 5.5 costs 40% less on typical workloads and produces output more than 30% faster.

Mixed reasoning results

The comparison used identical prompts through Anthropic’s API, with adaptive thinking enabled at the default effort level. Each problem was run once per model. Both systems completed a logic-grid puzzle correctly and returned the same correct results for a stone-removal game. On the constrained-ordering problem, neither produced an answer, even after the output allowance was increased.

Faster, but below the claim

Opus 5.5 completed the logic-grid task in 65 seconds for $0.16, versus 108 seconds and $0.27 for Opus 5. On the stone game, it used 28,740 output tokens and cost $0.58, while Opus 5 used 74,981 tokens and cost $1.88. Across the calls, the newer model averaged 103.4 output tokens per second against 93.1 for Opus 5, an improvement of about 11%, below Anthropic’s stated 30% figure.

Long failures still matter

The ordering test exposed a practical limitation: both models spent extensive time thinking without producing a result. With a 128,000-token limit, Opus 5.5 ran for 19 minutes, consumed 112,733 tokens and ended with a refusal stop reason. The source argues that this appeared to be an erroneous safety-filter response to a harmless counting problem. The results support lower costs for some workloads, but they do not establish better reasoning from this limited, single-run comparison.

AI-generated editorial illustration; not a documentary photograph.

Source: Claude Opus 5.5 vs. Opus 5 on reasoning tasks: Cheaper, faster, but not better

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