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Claude Opus 4.8

Sharper reasoning, more honest output, and the best agentic performance the company has shipped.
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Claude Opus 4.8

Across the tested dimensions — coding, agentic task completion, knowledge work, reasoning, and computer use — Opus 4.8 either matches or improves on its predecessor, and frequently outperforms competing frontier models.

What is Claude Opus 4.8?

Claude Opus 4.8 is the latest version of Anthropic's top-tier AI model, succeeding Claude Opus 4.7. Rather than a ground-up redesign, it represents a focused, meaningful upgrade — one that compounds on strong foundations with measurable improvements across coding, reasoning, agentic reliability, and what Anthropic calls honesty: the model's willingness to surface uncertainty rather than paper over gaps with confident-sounding approximations.

  • 4× Less likely to overlook flaws in its own generated code versus Opus 4.7
  • 84% Online-Mind2Web score best computer-use and browser-agent result tested
  • >10% Legal Agent Benchmarkfirst model to break this threshold on all-pass standard

Where Opus 4.8 excels

Coding and software engineering

Multiple engineering teams report that Opus 4.8 is more reliable as an autonomous coding assistant. It asks sharper clarifying questions before making large changes, pushes back when plans seem flawed, and catches more of its own mistakes before they propagate. On CursorBench — a rigorous evaluation from the Cursor team covering full end-to-end development tasks, Opus 4.8 outperformed all prior Opus models at every effort level. Tool calling is more efficient too, completing the same work with fewer intermediate steps.

Agentic task completion

In complex, multi-step autonomous workflows, Opus 4.8 shows the reliability characteristics that production AI agent deployments depend on. On a Super-Agent benchmark developed by one external partner, it was the only model to complete every case end-to-end, outperforming prior Opus versions and GPT-5.5 at equivalent cost. It's consistently better at carrying context across long sessions and following stylistic or technical direction without drift.

Legal and professional knowledge work

Opus 4.8 is the first model to surpass 10% on the all-pass standard of the Legal Agent Benchmark — a significant threshold in an industry where accuracy errors carry real professional consequences. Multiple legal AI platforms report that the improvement in consistency and reasoning quality translates directly into confidence about which attorney tasks can be delegated to AI-assisted workflows.

Computer use and browser automation

With an 84% score on Online-Mind2Web, Opus 4.8 ranks as the strongest computer-use and browser-agent model tested by any external team at launch. It maintains focus across long, complex web-based tasks in ways that directly benefit real-world automation pipelines.

Financial analysis

For financial document workflows, processing dense filings, earnings reports, and structured data, Opus 4.8 maintains the quality of Opus 4.7 while improving citation precision, reducing token consumption on retrieval tasks, and proactively flagging anomalies in inputs and outputs that other models left for human reviewers to catch.

Benchmark Focus Area Opus 4.8 Result
Online-Mind2Web
Browser agent and computer-use capability 84%
Legal Agent Benchmark (all-pass)
Legal reasoning accuracy and reliability >10%
CursorBench
End-to-end software development workflows Best-in-class
Super-Agent Benchmark
Complex multi-step agentic execution 100% completion
Code flaw detection
Honesty, verification, and error detection 4× fewer missed flaws

Mid-Task System Prompt Updates

The Messages API now accepts system entries inside the messages array, not just at the top level. Developers can update Claude's instructions mid-task — changing permissions, token budgets, or environmental context — without breaking the prompt cache or routing the update through a user turn. This makes it substantially easier to build sophisticated, adaptive agent harnesses.

API Pricing

  • Input: $6.50 / MTok
  • Output: $32.50 / MTok
Prompt Caching
  • Write: $8.13 / MTok
  • Read:  $0.65 / MTok

Who is Opus 4.8 built for?

Opus 4.8 is Anthropic's flagship model, positioned for work where quality is the primary constraint and cost is secondary. It's the right choice when you're building production-grade AI agents, handling high-stakes professional knowledge work, or need a model that can sustain coherent context and judgment across very long sessions.

  • Software engineering teams building autonomous coding agents or running large-scale codebase migrations with Claude Code
  • Legal technology companies where citation precision, reasoning quality, and accuracy thresholds matter at the case level
  • Financial services platforms processing dense unstructured documents where the model needs to flag its own uncertainties
  • AI product teams building multi-step agentic pipelines that run autonomously for extended periods
  • Enterprise research and analysis workflows requiring high-density, reliable outputs across long context windows
  • Multimodal document workflows — Opus 4.8 reasons over PDFs, diagrams, and unstructured visual content at 61% lower token cost than Opus 4.7

Common questions

Is Claude Opus 4.8 better than GPT-5.5?

On agentic benchmarks, Opus 4.8 outperforms GPT-5.5 in specific evaluations: one external partner's Super-Agent benchmark showed Opus 4.8 completing every case that GPT-5.5 could not, at cost parity. On computer use (Online-Mind2Web), Opus 4.8's 84% score beats GPT-5.5's reported result on the same evaluation. Comparative performance varies by task type; users with specific workloads should run their own evaluations.

What changed from Opus 4.7 to Opus 4.8?

The headline improvements are better honesty (Opus 4.8 flags uncertainties and code flaws at a significantly higher rate), improved judgment in autonomous tasks, more efficient tool calling, and better alignment scores. Verbose comment generation and tool-calling inconsistencies reported with Opus 4.7 are addressed in this release.

What is dynamic workflows in Claude Code?

Dynamic workflows let Claude plan a large software task and then execute it by spinning up hundreds of parallel subagents within a single Claude Code session. It verifies its outputs before surfacing results. It's currently in research preview and available on Enterprise, Team, and Max plans.

How does Opus 4.8 compare on multimodal tasks?

Opus 4.8 can reason over PDFs, diagrams, charts, and other unstructured visual content. For document-heavy workflows, it delivers this at a 61% lower token cost compared to Opus 4.7, according to one enterprise data platform's internal benchmarks.

What is Claude Opus 4.8?

Claude Opus 4.8 is the latest version of Anthropic's top-tier AI model, succeeding Claude Opus 4.7. Rather than a ground-up redesign, it represents a focused, meaningful upgrade — one that compounds on strong foundations with measurable improvements across coding, reasoning, agentic reliability, and what Anthropic calls honesty: the model's willingness to surface uncertainty rather than paper over gaps with confident-sounding approximations.

  • 4× Less likely to overlook flaws in its own generated code versus Opus 4.7
  • 84% Online-Mind2Web score best computer-use and browser-agent result tested
  • >10% Legal Agent Benchmarkfirst model to break this threshold on all-pass standard

Where Opus 4.8 excels

Coding and software engineering

Multiple engineering teams report that Opus 4.8 is more reliable as an autonomous coding assistant. It asks sharper clarifying questions before making large changes, pushes back when plans seem flawed, and catches more of its own mistakes before they propagate. On CursorBench — a rigorous evaluation from the Cursor team covering full end-to-end development tasks, Opus 4.8 outperformed all prior Opus models at every effort level. Tool calling is more efficient too, completing the same work with fewer intermediate steps.

Agentic task completion

In complex, multi-step autonomous workflows, Opus 4.8 shows the reliability characteristics that production AI agent deployments depend on. On a Super-Agent benchmark developed by one external partner, it was the only model to complete every case end-to-end, outperforming prior Opus versions and GPT-5.5 at equivalent cost. It's consistently better at carrying context across long sessions and following stylistic or technical direction without drift.

Legal and professional knowledge work

Opus 4.8 is the first model to surpass 10% on the all-pass standard of the Legal Agent Benchmark — a significant threshold in an industry where accuracy errors carry real professional consequences. Multiple legal AI platforms report that the improvement in consistency and reasoning quality translates directly into confidence about which attorney tasks can be delegated to AI-assisted workflows.

Computer use and browser automation

With an 84% score on Online-Mind2Web, Opus 4.8 ranks as the strongest computer-use and browser-agent model tested by any external team at launch. It maintains focus across long, complex web-based tasks in ways that directly benefit real-world automation pipelines.

Financial analysis

For financial document workflows, processing dense filings, earnings reports, and structured data, Opus 4.8 maintains the quality of Opus 4.7 while improving citation precision, reducing token consumption on retrieval tasks, and proactively flagging anomalies in inputs and outputs that other models left for human reviewers to catch.

Benchmark Focus Area Opus 4.8 Result
Online-Mind2Web
Browser agent and computer-use capability 84%
Legal Agent Benchmark (all-pass)
Legal reasoning accuracy and reliability >10%
CursorBench
End-to-end software development workflows Best-in-class
Super-Agent Benchmark
Complex multi-step agentic execution 100% completion
Code flaw detection
Honesty, verification, and error detection 4× fewer missed flaws

Mid-Task System Prompt Updates

The Messages API now accepts system entries inside the messages array, not just at the top level. Developers can update Claude's instructions mid-task — changing permissions, token budgets, or environmental context — without breaking the prompt cache or routing the update through a user turn. This makes it substantially easier to build sophisticated, adaptive agent harnesses.

API Pricing

  • Input: $6.50 / MTok
  • Output: $32.50 / MTok
Prompt Caching
  • Write: $8.13 / MTok
  • Read:  $0.65 / MTok

Who is Opus 4.8 built for?

Opus 4.8 is Anthropic's flagship model, positioned for work where quality is the primary constraint and cost is secondary. It's the right choice when you're building production-grade AI agents, handling high-stakes professional knowledge work, or need a model that can sustain coherent context and judgment across very long sessions.

  • Software engineering teams building autonomous coding agents or running large-scale codebase migrations with Claude Code
  • Legal technology companies where citation precision, reasoning quality, and accuracy thresholds matter at the case level
  • Financial services platforms processing dense unstructured documents where the model needs to flag its own uncertainties
  • AI product teams building multi-step agentic pipelines that run autonomously for extended periods
  • Enterprise research and analysis workflows requiring high-density, reliable outputs across long context windows
  • Multimodal document workflows — Opus 4.8 reasons over PDFs, diagrams, and unstructured visual content at 61% lower token cost than Opus 4.7

Common questions

Is Claude Opus 4.8 better than GPT-5.5?

On agentic benchmarks, Opus 4.8 outperforms GPT-5.5 in specific evaluations: one external partner's Super-Agent benchmark showed Opus 4.8 completing every case that GPT-5.5 could not, at cost parity. On computer use (Online-Mind2Web), Opus 4.8's 84% score beats GPT-5.5's reported result on the same evaluation. Comparative performance varies by task type; users with specific workloads should run their own evaluations.

What changed from Opus 4.7 to Opus 4.8?

The headline improvements are better honesty (Opus 4.8 flags uncertainties and code flaws at a significantly higher rate), improved judgment in autonomous tasks, more efficient tool calling, and better alignment scores. Verbose comment generation and tool-calling inconsistencies reported with Opus 4.7 are addressed in this release.

What is dynamic workflows in Claude Code?

Dynamic workflows let Claude plan a large software task and then execute it by spinning up hundreds of parallel subagents within a single Claude Code session. It verifies its outputs before surfacing results. It's currently in research preview and available on Enterprise, Team, and Max plans.

How does Opus 4.8 compare on multimodal tasks?

Opus 4.8 can reason over PDFs, diagrams, charts, and other unstructured visual content. For document-heavy workflows, it delivers this at a 61% lower token cost compared to Opus 4.7, according to one enterprise data platform's internal benchmarks.

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