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Anthropic: Claude Opus 5.5 (batch)

anthropic/claude-opus-5.5:batch

比较

Claude Opus 5.5 is Anthropic's flagship model for demanding reasoning, coding, and long-horizon agentic work, succeeding Claude Opus 5. It is particularly strong at multi-step changes in large codebases, code review and bug finding, financial and scientific analysis, and reading dense charts, diagrams, and screenshots, and it is more careful than its predecessor about only stating figures and citing sources it can back up.

The model completes comparable tasks in fewer steps and with fewer tokens than Opus 5, and reports on its work in plainer language, with clear updates on what it did, what it found, and what it needs from the user. Thinking is always adaptive, so effort is the main lever for trading off depth, latency, and cost, and lower effort settings remain effective for latency-sensitive workloads.

模态
输入 / 输出价格
US$2 / US$10每 1M
上下文
1.0M
发布时间
2026年9月22日
比较
提供商定价性能正常运行时间基准测试应用活动文档常见问题探索

提供商

不同公司托管同一个模型。OpenRouter 会根据您选择的路由模式,将您的请求路由到其中一家公司:Balanced(价格 + 速度)、Nitro(最快)或 Floor(最便宜)。

定价

客户为此模型实际支付的平均价格,与提供商公布的价格并列展示。由于缓存和折扣,实际支付的价格往往远低于标价。

性能

吞吐量是模型生成内容的速度(每秒 token 数,越高越好)。延迟是完整的往返时间(越低越好)。TTFT 是首个 token 的响应时间,即您看到内容出现前需要等待的时间(越低越好)。

正常运行时间

正常运行时间是指过去 3 天中至少有一家提供商响应请求的时间百分比。可用性是指成功提供推理服务的时间百分比。OpenRouter 会持续监控,并在某家提供商返回错误时使用次优提供商。

基准测试

标准化评测得分,以及此模型针对共用基准测试提示词的实际输出。百分比越高越好,每项排名显示此模型在该来源所评测的模型中的位置。

基准测试得分摘要: Anthropic: Claude Opus 5.5 (batch) (Artificial Analysis、Design Arena 和 Vals AI)
来源基准测试得分
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) Intelligence Index57.0
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) HLE57.5%
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) AA-LCR84.7%
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) GDPval-AA66.8%
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) CritPt31.7%
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) SciCode65.0%
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) Terminal-Bench 4.059.6%
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) AA-Omniscience Accuracy65.5%
Artificial AnalysisClaude Opus 5.5 (Xhigh, Default Fallback) AA-Omniscience Non-Hallucination Rate35.0%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) Intelligence Index48.1
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) HLE54.7%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) AA-LCR84.3%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) GDPval-AA54.6%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) CritPt27.7%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) SciCode59.3%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) Terminal-Bench 4.052.5%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) AA-Omniscience Accuracy63.9%
Artificial AnalysisClaude Opus 5.5 (Medium, Default Fallback) AA-Omniscience Non-Hallucination Rate33.1%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) Intelligence Index34.5
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) HLE48.3%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) AA-LCR80.7%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) GDPval-AA37.0%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) CritPt17.7%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) SciCode58.6%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) Terminal-Bench 4.031.3%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) AA-Omniscience Accuracy63.3%
Artificial AnalysisClaude Opus 5.5 (Low, Default Fallback) AA-Omniscience Non-Hallucination Rate33.7%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) Intelligence Index51.7
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) HLE55.6%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) AA-LCR82.7%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) GDPval-AA60.7%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) CritPt30.9%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) SciCode60.4%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) Terminal-Bench 4.056.6%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) AA-Omniscience Accuracy64.8%
Artificial AnalysisClaude Opus 5.5 (High, Default Fallback) AA-Omniscience Non-Hallucination Rate36.1%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) Intelligence Index58.4
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) HLE61.4%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) AA-LCR84.7%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) GDPval-AA68.3%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) CritPt31.7%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) SciCode66.9%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) Terminal-Bench 4.059.6%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) AA-Omniscience Accuracy65.5%
Artificial AnalysisClaude Opus 5.5 (Max, Default Fallback) AA-Omniscience Non-Hallucination Rate49.7%
Design ArenaClaude Opus 5.5 Agents Arena Blender3d Elo1281
Design ArenaClaude Opus 5.5 Agents Arena Mobile Apps Elo1309
Design ArenaClaude Opus 5.5 Agents Arena Pdf Elo1319
Design ArenaClaude Opus 5.5 Agents Arena Spreadsheet Elo1392
Design ArenaClaude Opus 5.5 Agents Arena Webapps Elo1309
Design ArenaClaude Opus 5.5 Models Arena 3D Elo1471
Design ArenaClaude Opus 5.5 Models Arena Asciiart Elo1354
Design ArenaClaude Opus 5.5 Models Arena Code Categories Elo1385
Design ArenaClaude Opus 5.5 Models Arena Data Visualization Elo1394
Design ArenaClaude Opus 5.5 Models Arena Game Development Elo1434
Design ArenaClaude Opus 5.5 Models Arena SVG Elo1323
Design ArenaClaude Opus 5.5 Models Arena UI Component Elo1378
Design ArenaClaude Opus 5.5 Models Arena Website Elo1325
Vals AIClaude Opus 5.5 BioMysteryBench79.3%
Vals AIClaude Opus 5.5 ClaimBench100.0%
Vals AIClaude Opus 5.5 Code Migration v1.181.0%
Vals AIClaude Opus 5.5 CyberBench v1.155.4%
Vals AIClaude Opus 5.5 EMB v1.175.8%
Vals AIClaude Opus 5.5 Finance Agent v2.167.8%
Vals AIClaude Opus 5.5 Vals Finance Index65.6%
Vals AIClaude Opus 5.5 HLAB-Vals-1.19.2%
Vals AIClaude Opus 5.5 Immigration72.1%
Vals AIClaude Opus 5.5 IOI95.1%
Vals AIClaude Opus 5.5 Vals Legal Index72.3%
Vals AIClaude Opus 5.5 Legal Research Bench50.5%
Vals AIClaude Opus 5.5 MedCode49.8%
Vals AIClaude Opus 5.5 MedScribe91.4%
Vals AIClaude Opus 5.5 MysteryMechanism49.5%
Vals AIClaude Opus 5.5 ProgramBench18.5%
Vals AIClaude Opus 5.5 ProofBench v1.1100.0%
Vals AIClaude Opus 5.5 Public Benefits Bench v1.170.6%
Vals AIClaude Opus 5.5 Robo-bench14.6%
Vals AIClaude Opus 5.5 Vals RSI Index37.3%
Vals AIClaude Opus 5.5 SAGE91.3%
Vals AIClaude Opus 5.5 Vals Science Index58.7%
Vals AIClaude Opus 5.5 SRE Bench33.6%
Vals AIClaude Opus 5.5 SWE-bench Multimodal70.2%
Vals AIClaude Opus 5.5 Tax Agent Bench45.6%
Vals AIClaude Opus 5.5 Terminal-Bench 4.065.2%
Vals AIClaude Opus 5.5 Terminal-Bench-Science47.1%
Vals AIClaude Opus 5.5 Vals Index70.2%
Vals AIClaude Opus 5.5 Vibe Code Bench 1-10030.4%
Vals AIClaude Opus 5.5 Vibe Code Bench v1.190.3%

应用

向此模型发送最多流量的公开应用。这能很好地反映实际生产工作负载的情况,也能提示此模型最适合哪些用例。

活动

此模型的 token 用量和请求流量随时间的变化。

API

可直接用于调用此模型的代码。OpenRouter 的 API 与 OpenAI 兼容——大多数 SDK 只需替换基础 URL 即可使用。切换模型时,唯一需要更改的是下方的模型标识符。

Anthropic: Claude Opus 版本

目前无法通过 EU 区域内路由使用。 区域内路由文档

文档

在 OpenRouter 上使用 Anthropic: Claude Opus 5.5 (batch) 构建应用的指南、实用教程、博客文章和工具。

  • Claude 5.5 Migration Guide实用示例
  • Claude Opus vs Sonnet vs Haiku: Which Should You Use?博客文章
  • How Much Does Claude Code Cost? Real Session Costs by Model博客文章
  • Hit Your Claude Code Usage Limit? How to Keep Coding博客文章
  • Claude 529 Overloaded: What It Means and How to Fix It博客文章

探索更多模型

具备视觉能力的 AI 模型:用于图像理解的多模态大语言模型集合AI 模型排行榜排名
US$2.00US$10.00US$0.10----
--
AutoExacto 基准测试
GPQA DiamondTAU-BenchAmazon Bedrock90.0%76.7%Claude Platform on AWS89.8%76.1%Azure90.3%75.4%auto-routing90.1%75.6%Google Vertex90.0%75.7%Azure89.7%75.8%Amazon Bedrock89.9%75.5%Amazon Bedrock90.4%74.6%Google Vertex89.9%74.7%Google Vertex89.9%73.7%
+1 家其他提供商

正常运行时间数据尚不足,暂时无法显示。

当上游提供商发生错误时,如果您的请求筛选条件允许,我们可以通过路由到另一家健康的提供商来恢复服务。您可以通过以下接口以编程方式访问各提供商的正常运行时间数据: 端点 API。了解更多有关我们的 负载均衡和提供商路由选项。

使用此模型的应用尚无足够数据。

常见问题

Claude Opus 5.5 is Anthropic's flagship model for demanding reasoning, coding, and long-horizon agentic work, succeeding Claude Opus 5. It is particularly strong at multi-step changes in large codebases, code review and bug finding, financial and scientific analysis, and reading dense charts, diagrams, and screenshots, and it is more careful than its predecessor about only stating figures and...

OpenRouter 上的 Claude Opus 5.5 (batch) 文档包括 Claude 5.5 Migration Guide 实用指南、Claude Opus vs Sonnet vs Haiku: Which Should You Use? 博客文章、How Much Does Claude Code Cost? Real Session Costs by Model 博客文章、Hit Your Claude Code Usage Limit? How to Keep Coding 博客文章和Claude 529 Overloaded: What It Means and How to Fix It 博客文章。快速入门介绍了 API 密钥和您的首次请求,API 参考列出了所有参数。

Claude Opus 5.5 (batch) 的费用为 US$2.00/百万输入 token 和 US$10.00/百万输出 token,Cache Read,价格为 US$0.10/M tokens、Cache Write,价格为 US$2.50/M tokens、Cache Write (1h),价格为 US$4.00/M tokens和Web Search,价格为 US$10.00/1K calls 单独计费。

Claude Opus 5.5 (batch) 的上下文窗口为 1,000,000 个 token。它最多支持 128,000 个补全 token。

是的。Claude Opus 5.5 (batch) 接受 tools 和 tool_choice,以进行函数调用。 它还支持通过 response_format 中的 JSON schema 实现结构化输出。

Claude Opus 5.5 (batch) 接受 文本、图像和PDF 等文件 作为输入,并返回 文本。

Claude Haiku 5.5, Claude Sonnet 5.5, Claude Fable 5.1 及另外 11 个 是 Anthropic 的其他 文本 模型。

Claude Opus 5.5 (batch) 于 2026年9月22日 发布。

更多模型,来自 Anthropic

Claude Haiku 5.5

Claude Haiku 5.5 is Anthropic's small, fast model for high-volume, cost-sensitive work such as summarization, subagents, and browser use. It succeeds Claude Haiku 4.5 with stronger coding, computer use, and knowledge work, and accepts text and image input with a 1M-token context window.

It is the first Haiku model with adjustable effort. Thinking is adaptive and on by default, with effort as the main lever for trading off depth, latency, and cost; it can be turned off at low, medium, and high effort.

文本1M 上下文US$0.10 / US$0.50
Claude Haiku 5.5 (batch)

Claude Haiku 5.5 is Anthropic's small, fast model for high-volume, cost-sensitive work such as summarization, subagents, and browser use. It succeeds Claude Haiku 4.5 with stronger coding, computer use, and knowledge work, and accepts text and image input with a 1M-token context window.

It is the first Haiku model with adjustable effort. Thinking is adaptive and on by default, with effort as the main lever for trading off depth, latency, and cost; it can be turned off at low, medium, and high effort.

文本1M 上下文US$0.05 / US$0.25
Claude Sonnet 5.5

Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, succeeding Claude Sonnet 5 as a direct upgrade. It is especially strong at building features, fixing bugs, and producing polished documents, slides, and spreadsheets, and it writes and communicates more clearly than its predecessor.

Thinking is always on, so effort is the main lever for trading off depth, latency, and cost, and lower effort settings keep it responsive for everyday agentic loops.

文本1M 上下文US$2 / US$10
Claude Sonnet 5.5 (batch)

Claude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, succeeding Claude Sonnet 5 as a direct upgrade. It is especially strong at building features, fixing bugs, and producing polished documents, slides, and spreadsheets, and it writes and communicates more clearly than its predecessor.

Thinking is always on, so effort is the main lever for trading off depth, latency, and cost, and lower effort settings keep it responsive for everyday agentic loops.

文本1M 上下文US$1 / US$5
Claude Opus 5.5

Claude Opus 5.5 is Anthropic's flagship model for demanding reasoning, coding, and long-horizon agentic work, succeeding Claude Opus 5. It is particularly strong at multi-step changes in large codebases, code review and bug finding, financial and scientific analysis, and reading dense charts, diagrams, and screenshots, and it is more careful than its predecessor about only stating figures and citing sources it can back up.

The model completes comparable tasks in fewer steps and with fewer tokens than Opus 5, and reports on its work in plainer language, with clear updates on what it did, what it found, and what it needs from the user. Thinking is always adaptive, so effort is the main lever for trading off depth, latency, and cost, and lower effort settings remain effective for latency-sensitive workloads.

文本1M 上下文US$4 / US$20
Claude Opus 5.5 (batch)

Claude Opus 5.5 is Anthropic's flagship model for demanding reasoning, coding, and long-horizon agentic work, succeeding Claude Opus 5. It is particularly strong at multi-step changes in large codebases, code review and bug finding, financial and scientific analysis, and reading dense charts, diagrams, and screenshots, and it is more careful than its predecessor about only stating figures and citing sources it can back up.

The model completes comparable tasks in fewer steps and with fewer tokens than Opus 5, and reports on its work in plainer language, with clear updates on what it did, what it found, and what it needs from the user. Thinking is always adaptive, so effort is the main lever for trading off depth, latency, and cost, and lower effort settings remain effective for latency-sensitive workloads.

文本1M 上下文US$2 / US$10
Claude Fable 5.1

Claude Fable 5.1 improves on Claude Fable 5 across the board, with the biggest gains in agentic coding, long-running agentic workflows, and knowledge work: long code refactors, front-end and visual code generation, and finance and analysis tasks in particular. It also tends to be more concise than Fable 5 in its plans and summaries. We recommend testing it as a direct upgrade wherever you use Fable 5 today, and alongside Opus 5 on reasoning-heavy tasks.

文本1M 上下文US$10 / US$50
Claude Fable 5.1 (batch)

Claude Fable 5.1 improves on Claude Fable 5 across the board, with the biggest gains in agentic coding, long-running agentic workflows, and knowledge work: long code refactors, front-end and visual code generation, and finance and analysis tasks in particular. It also tends to be more concise than Fable 5 in its plans and summaries. We recommend testing it as a direct upgrade wherever you use Fable 5 today, and alongside Opus 5 on reasoning-heavy tasks.

文本1M 上下文US$5 / US$25
Claude Opus 5

Fast-mode variant of Opus 5 - identical capabilities with higher output speed at 2x pricing relative to regular Opus 5.

Learn more in Anthropic's docs: https://platform.claude.com/docs/en/build-with-claude/fast-mode

Note: As of September 1, 2026, this dedicated fast model is deprecated. Fast mode is now served by the fast service tier endpoint on Claude Opus 5 — request it with service_tier: "fast" or speed: "fast". Requests to this model keep working and are served by the same fast tier capacity, so no action is required, but new integrations should target the regular model. Learn more in our service tier docs: https://openrouter.ai/docs/guides/features/service-tiers

文本1M 上下文
Claude Opus 5

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 of charts and documents, complex office deliverables, and coordinating parallel subagents.

The model maintains strong instruction following and tool use across extended tasks, while remaining effective at lower effort settings for workloads that prioritize latency and token efficiency.

文本1M 上下文US$5 / US$25
Claude Opus 5 (batch)

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 of charts and documents, complex office deliverables, and coordinating parallel subagents.

The model maintains strong instruction following and tool use across extended tasks, while remaining effective at lower effort settings for workloads that prioritize latency and token efficiency.

文本1M 上下文US$2.50 / US$12.50
Claude Sonnet 5

Sonnet 5 is Anthropic's most capable Sonnet-class model, with frontier performance across coding, agents, and professional work. It supports adaptive thinking with selectable reasoning effort levels (low, medium, high, max, and x-high), a 1M-token context window, and text, image, and file inputs. Sonnet 5 uses an updated tokenizer and includes real-time cyber safeguards that block certain high-risk dual-use activities.

文本1M 上下文US$2 / US$10
Claude Sonnet 5 (batch)

Sonnet 5 is Anthropic's most capable Sonnet-class model, with frontier performance across coding, agents, and professional work. It supports adaptive thinking with selectable reasoning effort levels (low, medium, high, max, and x-high), a 1M-token context window, and text, image, and file inputs. Sonnet 5 uses an updated tokenizer and includes real-time cyber safeguards that block certain high-risk dual-use activities.

文本1M 上下文US$1 / US$5
Claude Fable Latest

This model always redirects to the latest model in the Claude Fable family.

文本1M 上下文
Claude Fable 5

Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token context window. It is suited for long-running, complex, and asynchronous tasks that previously required frequent human check-ins.

It is particularly strong at end-to-end work that would otherwise take a person hours, days, or weeks - taking on problems that are long-running, ambiguous, or highly multi-step. It executes well-scoped tasks with few mistakes, automatically self-correcting through verification loops, and ships with robust safeguards.

文本1M 上下文US$10 / US$50
Claude Fable 5 (batch)

Claude Fable 5 is a Mythos-class model from Anthropic, built for autonomous knowledge work and coding. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token context window. It is suited for long-running, complex, and asynchronous tasks that previously required frequent human check-ins.

It is particularly strong at end-to-end work that would otherwise take a person hours, days, or weeks - taking on problems that are long-running, ambiguous, or highly multi-step. It executes well-scoped tasks with few mistakes, automatically self-correcting through verification loops, and ships with robust safeguards.

文本1M 上下文US$5 / US$25
Claude Opus 4.8

Fast-mode variant of Opus 4.8 - identical capabilities with higher output speed at 2x pricing relative to regular Opus 4.8.

Learn more in Anthropic's docs: https://platform.claude.com/docs/en/build-with-claude/fast-mode

Note: As of September 1, 2026, this dedicated fast model is deprecated. Fast mode is now served by the fast service tier endpoint on Claude Opus 4.8 — request it with service_tier: "fast" or speed: "fast". Requests to this model keep working and are served by the same fast tier capacity, so no action is required, but new integrations should target the regular model. Learn more in our service tier docs: https://openrouter.ai/docs/guides/features/service-tiers

文本1M 上下文
Claude Opus 4.8

Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token context window. It is suited for highly autonomous agents, long-horizon agentic work, knowledge work, and memory-driven tasks where coherence over extended sessions matters.

It is particularly strong on multi-step reasoning, complex coding, and end-to-end project orchestration - large codebases, multi-stage debugging, and long-running asynchronous agent pipelines. Beyond coding, it handles knowledge work such as drafting documents, building presentations, and analyzing data, maintaining quality across very long outputs.

文本1M 上下文US$5 / US$25
Claude Opus 4.8 (batch)

Claude Opus 4.8 is Anthropic's most capable generally available model in the Opus family. It supports text, image, and file inputs with text output, with reasoning support and a 1M-token context window. It is suited for highly autonomous agents, long-horizon agentic work, knowledge work, and memory-driven tasks where coherence over extended sessions matters.

It is particularly strong on multi-step reasoning, complex coding, and end-to-end project orchestration - large codebases, multi-stage debugging, and long-running asynchronous agent pipelines. Beyond coding, it handles knowledge work such as drafting documents, building presentations, and analyzing data, maintaining quality across very long outputs.

文本1M 上下文US$2.50 / US$12.50
Claude Opus 4.7

Fast-mode variant of Opus 4.7 - identical capabilities with higher output speed at premium 6x pricing.

Learn more in Anthropic's docs: https://platform.claude.com/docs/en/build-with-claude/fast-mode

文本1M 上下文