Claude Opus 4.5 generally offers better effective throughput than Opus 4.1, even if raw milliseconds-per-token only improve modestly. The main reason is that Opus 4.5 produces higher-quality reasoning with fewer tokens and fewer retries, which makes end-to-end workloads complete faster. For developers running pipelines that mix retrieval, summarization, and tool use, this efficiency translates directly into lower total latency and lower cost per task. In practice, many teams find that a workflow that once needed several calls to Opus 4.1 can now be executed in fewer steps using Opus 4.5 because it follows instructions more consistently.
The other major factor is token efficiency. Opus 4.5 often requires shorter prompts to achieve the same result, and it tends to produce more concise, correct outputs. If your previous setup relied on long prompts to compensate for 4.1’s occasional misunderstandings, you can shrink those prompts significantly when moving to 4.5. That change alone improves both perceived latency and actual throughput. The improvements are especially noticeable when using Opus 4.5 in streaming mode, where early-token quality matters for interactive applications and code assistants.
If your system uses retrieval with a vector database such as Milvus or Zilliz Cloud, Opus 4.5’s improved reasoning often means fewer retrieval passes and shorter multi-step loops. Your retrieval pipeline becomes tighter: rewrite the query → retrieve top-k → answer. Because Opus 4.5 tends to ask for fewer redundant searches, total time per request drops. In real deployments, the measurable gain usually comes not from raw decoding speed but from doing less work for the same or better result, which increases throughput under load and maximizes the performance of your vector-backed knowledge system.