anthropic
Anthropic: Claude Opus 4.5
anthropic/claude-opus-4.5
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter's catalog presents anthropic/claude-opus-4.5 as an Anthropic Opus-class model aimed at difficult software engineering, agentic workflows, and extended computer-use tasks. The catalog lists text, image, and file inputs with text output, a large context window, and support for tools, structured outputs, streaming controls, and optional reasoning-related parameters. Because this source pack contains only catalog data and no independent model card, treat capability and positioning claims as provider-catalog assertions and validate them on representative workloads.[1]
Strengths
- Catalog-reported multimodal input across text, images, and files, with text generation for engineering and agent-style tasks.[1]
- Large listed context window may help with long documents, repositories, and multi-step sessions.[1]
- Supported parameters include tools, tool choice, structured outputs, response format, and reasoning controls.[1]
Limitations
- Evidence is catalog-only; an independent model card was not available in this source pack.[1]
- Output is listed as text only, so teams needing image, audio, or file generation should look elsewhere.[1]
- Arena-style measurements and catalog positioning need workload-specific validation before adoption.[1]
Where to use it
- May suit complex coding assistance, refactoring, debugging, and repository-scale analysis where long context matters.[1]
- Potential fit for agentic tool-using workflows that benefit from structured outputs and explicit tool control.[1]
- Could be evaluated for image-or-file-to-text workflows such as design review, document extraction, and technical triage.[1]
Sources
- [1] OpenRouter catalog · Anthropic: Claude Opus 4.5Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance across real-world coding and...
Specifications
- Model ID
- anthropic/claude-opus-4.5
- Canonical ID
- anthropic/claude-4.5-opus-20251124
- Creator
- anthropic
- Added to OpenRouter
- 24.11.2025
- Context length
- 200,000
- Modality
- text+image+file->text
- Input modalities
- file, image, text
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $5 / out $25
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: optional · parameters: include_reasoning, reasoning |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · parameters: include_reasoning, reasoning |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Design Arena | models · 3dwin rate 58.5% · rank 50 | 1,196Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · asciiartwin rate 54.8% · rank 31 | 1,185Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 59.5% · rank 49 | 1,233Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 58.5% · rank 38 | 1,241Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 59.3% · rank 47 | 1,219Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 58.7% · rank 41 | 1,171Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 58.1% · rank 49 | 1,229Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 59.7% · rank 50 | 1,240Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · androidnativewin rate 65.5% · rank 24 | 1,162Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · fullstackwin rate 60.1% · rank 26 | 1,134Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 60.7% · rank 24 | 1,183Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · webappswin rate 55.1% · rank 32 | 1,141Elo | CC — below the B band | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Claude Platform on AWS | 200,000 | $5 | $25 | — | — | 100% |
| Azure | 200,000 | $5 | $25 | — | — | — |
| 200,000 | $5 | $25 | — | — | — | |
| Amazon Bedrock | 200,000 | $5 | $25 | — | — | 100% |
| Anthropic | 200,000 | $5 | $25 | — | — | 100% |
| Amazon Bedrock | 200,000 | $5.5 | $27.5 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.