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Model details

Claude Opus 4.8 (Anthropic)

Claude Opus 4.8 sits at the top of Anthropic's Claude family, designed for demanding agentic workflows, complex reasoning, and multi-step coding runs that require sustained performance. It builds directly on Opus 4.7 with improvements across a wide range of capability evaluations covering coding, agentic tasks, reasoning, and practical knowledge work, as detailed in the accompanying system card. Early testers report noticeably sharper judgment and greater reliability when the model is collaborating on agentic tasks, with Anthropic positioning this release less around raw benchmark gains and more around honest collaboration: the model is tuned to express uncertainty, flag its own mistakes, and tell users when it does not have a confident answer.

Beyond the core model, Opus 4.8 launches alongside a set of platform features that shape how it is used in practice. claude.ai gains user-facing effort controls for adjusting how much work Claude puts into a task, while Claude Code receives a new dynamic workflows feature aimed at tackling very large-scale problems. Fast mode for Opus 4.8 runs at roughly 2.5 times the speed of standard operation and is priced three times lower than the equivalent option on previous models, with Anthropic noting the flagship is available for the same overall price as its predecessor. Together these updates make the model a strong fit for long-running coding agents, research-heavy pipelines, and any workflow where transparent reasoning and dependable judgment matter more than maximum throughput.

LLM Gatewayanthropic/claude-opus-4-8claude-opus

Quick Info

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Provider
LLM Gateway
Model key
anthropic/claude-opus-4-8
Release date
May 28, 2026
Last updated
May 28, 2026
Knowledge cutoff
2026-01
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$5.00
Output token cost
$25.00

Limits

Output tokens
128,000 tokens
Context window
1,000,000 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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