Claude Opus 4.5 is positioned at the frontier of the Claude lineup for tasks requiring maximum intelligence, nuanced reasoning, and sophisticated instruction following. It is designed for the most demanding applications where quality is the primary constraint and cost is secondary — complex research synthesis, advanced coding projects, nuanced creative writing, and multi-step agentic workflows that require sustained coherent reasoning across many steps. It supports a 200K-token context window, vision inputs, tool use, and streaming.
Claude Opus 4.5 is priced at $15.00 per million input tokens and $75.00 per million output tokens — the most expensive model in Anthropic's lineup and among the most expensive in the industry. Prompt caching reduces repeated input to $1.50/1M. At 1,000 input + 500 output tokens per call, it costs approximately $0.0525 per 1,000 API calls — significantly more expensive than lower-tier models in the lineup. The cost premium is significant, and Opus 4.5 is not the right choice for high-volume workloads. It is best reserved for tasks where the quality difference versus cheaper models is measurable and valuable — typically complex reasoning, nuanced writing, and tasks requiring deep domain expertise.
Claude Opus 4.5 supports a 200K-token context window, matching other Claude models in the lineup. Latency is higher than Sonnet-tier models — median TTFT is approximately 800ms–1.5s under typical load, reflecting the larger model size. Throughput is approximately 40–60 tokens per second. Maximum output is 8,192 tokens in standard mode, with extended output available via beta access. For latency-sensitive applications, Claude 3.7 Sonnet in extended thinking mode often delivers comparable quality at lower cost and with more predictable latency. Opus 4.5 is best suited to batch or async workloads where quality matters more than speed.
Claude Opus 4.5 is best suited to tasks requiring the highest level of reasoning and instruction following: complex multi-document research synthesis, advanced software architecture design, nuanced creative writing with specific style requirements, sophisticated data analysis, and agentic workflows that must maintain coherent context and goals across dozens of tool calls. Its instruction following is among the most reliable available — it is less likely than smaller models to drift from complex instructions, ignore constraints, or produce outputs that technically satisfy the prompt but miss the intent. For applications where "almost right" is not acceptable, Opus 4.5's quality ceiling justifies its cost.
Claude Opus 4.5 sits at the top of Anthropic's lineup, above Claude 3.7 Sonnet and Claude 3.5 Sonnet. Its main competitors are frontier-tier models from OpenAI and Google at similar price points. For most production workloads, Claude 3.7 Sonnet in extended thinking mode delivers strong quality at a fraction of the cost — making Opus 4.5 a specialized tool rather than a general-purpose upgrade. The intelligence score of approximately 93/100 reflects top-tier capability across most benchmark categories. Always evaluate whether the quality improvement over 3.7 Sonnet is measurable on your specific task before committing to Opus 4.5 for production.
Composite quality score based on reasoning, coding, and instruction-following benchmarks.
Input price vs 135 frontier models tracked. Avg: $5.69/1M.
Industry-standard benchmarks grouped by capability. Higher is better. Hover a row for benchmark description.
| Model ID | claude-opus-4-5 |
| Provider | Anthropic |
| Model Family | Claude 4 |
| Tier | Frontier |
| Context Window | 200,000 tokens (200K) |
| Max Output Tokens | 32,000 tokens |
| Input Price | $15 / 1M tokens |
| Output Price | $75 / 1M tokens |
| Cached Input Price | $1.5 / 1M tokens |
| Throughput | 70 tokens/sec |
| Latency (P50) | 1.2s |
| Intelligence Score | 90/100 |
| LiveBench Score | 80/100 |
| Cost per Task (LiveBench) | $1.10 |
| Data Confidence | Supported |
| HLE Score | 40/100 |
| GPQA Diamond | 74/100 |
| SWE-bench Score | 72/100 |
| OSWorld Score | 83/100 |
| BrowseComp Score | 91/100 |
| Terminal-Bench Score | 88/100 |
| AutoBench Score | 26/100 |
| Parameters | — |
| Vision Support | Yes |
| Function Calling | Yes |
| Streaming | Yes |
| Reasoning Model | Yes |
| Open Weights | No |
| Data Source | Static (verified) |
| Last Updated | 2026-07-20 |
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