anthropic
Anthropic: Claude Opus 5 (batch)
anthropic/claude-opus-5:batch
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-5:batch as a batch variant associated with canonical ID anthropic/claude-opus-5-20260723. It lists text, image, and file inputs with text output, a one-million-token context window, optional reasoning enabled at high effort by default, and support for tools, structured outputs, verbosity, and response-format controls. The catalog description positions it for demanding reasoning, coding, long-horizon agentic work, software tasks, code review, bug finding, and visual analysis; it also reports measured arena and index results across coding, agentic, design, and related tasks. An independent model card was not included in the source pack.[1]
Strengths
Limitations
- Evidence is limited to OpenRouter’s catalog; no independent model card was supplied.[1]
- The source does not specify batch-specific execution behavior, latency, availability, quotas, or workload limits.[1]
- Arena and index measurements are aggregate catalog data, not evidence for any particular deployment; validate representative workloads.[1]
Where to use it
- Consider for complex coding, code review, or bug-finding workflows that benefit from reasoning controls and tools.[1]
- Potentially suitable for long-context analysis of text, images, or files when a text response is required.[1]
- May be evaluated for agentic or design-oriented tasks, with representative tests before production use.[1]
Sources
- [1] OpenRouter catalog · Anthropic: Claude Opus 5 (batch)Sources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
Claude Opus 5 is Anthropic’s flagship model for demanding reasoning, coding, and long-horizon agentic work. It is particularly strong at end-to-end software tasks, code review and bug finding, visual analysis...
Specifications
- Model ID
- anthropic/claude-opus-5:batch
- Canonical ID
- anthropic/claude-opus-5-20260723
- Creator
- anthropic
- Added to OpenRouter
- 24.07.2026
- Context length
- 1,000,000
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $2.5 / out $12.5
- 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 | AA — next 20% of the cohort | reasoning: optional · default high · efforts: max, xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | SS — top 10% of the cohort | — |
| Agents | SS — top 10% of the cohort | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · default high · efforts: max, xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| 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 |
|---|---|---|---|---|
| Artificial Analysis | Intelligence index | 44.2 | AA — next 20% of the cohort | 13.11.2026 |
| Artificial Analysis | Coding index | 78 | SS — top 10% of the cohort | 13.11.2026 |
| Artificial Analysis | Agentic index | 56.5 | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · agenticgamedevwin rate 53.3% · rank 3 | 1,203Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · androidnativewin rate 55.7% · rank 8 | 1,243Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · blender3dwin rate 63.1% · rank 5 | 1,201Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · codetovideowin rate 63.6% · rank 4 | 1,250Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · fullstackwin rate 57.1% · rank 6 | 1,286Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · godotgamedevwin rate 54.5% · rank 3 | 1,261Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 67.1% · rank 1 | 1,348Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | agents · pdfwin rate 57.2% · rank 11 | 1,231Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | agents · python-pptxslideswin rate 54.3% · rank 7 | 1,225Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · spreadsheetwin rate 57.1% · rank 9 | 1,239Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | agents · webappswin rate 54.8% · rank 12 | 1,253Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · 3dwin rate 59.9% · rank 15 | 1,324Elo | AA — next 20% of the cohort | 13.11.2026 |
| Design Arena | models · asciiartwin rate 68.6% · rank 1 | 1,354Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 57.4% · rank 12 | 1,318Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · datavizwin rate 58.3% · rank 9 | 1,327Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · gamedevwin rate 58% · rank 11 | 1,332Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 58.7% · rank 5 | 1,308Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 60.6% · rank 9 | 1,341Elo | SS — top 10% of the cohort | 13.11.2026 |
| Design Arena | models · websitewin rate 56.1% · rank 14 | 1,305Elo | AA — next 20% of the cohort | 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) |
|---|---|---|---|---|---|---|
| Anthropic | 1,000,000 | $2.5 | $12.5 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.