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Anthropic: Claude Opus 4.5Active

anthropic/claude-opus-4.5
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Claude Opus 4.5 is Anthropic's latest frontier reasoning model, purpose-built for complex software engineering, agentic workflows, and long-horizon computer use. It delivers strong multimodal capabilities, competitive performance on real-world coding and reasoning benchmarks, and improved robustness against prompt injection attacks. The model is designed to operate efficiently across varied effort levels, allowing developers to balance speed, depth, and token usage based on their specific task requirements—you can fine-tune token efficiency through the OpenRouter Verbosity parameter, which offers low, medium, and high settings. Beyond that, Opus 4.5 supports advanced tool use, extended context management, and coordinated multi-agent setups, making it ideal for autonomous research, debugging, multi-step planning, and spreadsheet or browser manipulation. Compared to previous Opus generations, it brings substantial improvements in structured reasoning, execution reliability, and alignment, while reducing token overhead and delivering more consistent performance on long-running tasks.

By:AnthropicInput Type:Output Type:Publish time:2025-11-24

Providers

Route requests across multiple providers. Copy a provider slug to set your preference.

ProviderCache Hit RateContext
Anthropic
anthropic
-$5/ M tokens$25/ M tokensRead:0.5/ M tokensWrite:6.25-10/ M tokens200K--
Google Vertex
google-vertex
67.0%$5/ M tokens$25/ M tokensRead:0.5/ M tokensWrite:6.25-10/ M tokens200K1.13s52.7tps
Amazon Bedrock
amazon-bedrock
-$5/ M tokens$25/ M tokensRead:0.5/ M tokensWrite:6.25-10/ M tokens200K--

Uptime

Direct request success rate on AI Gateway and per-provider.

Oct 26, 18:54
Google Vertex100.00%
Amazon Bedrock-

Throughput

P50 throughput on live AI Gateway traffic, in tokens per second (TPS).

Latency

P50 time to first token (TTFT) on live AI Gateway traffic, in milliseconds.

Activity

Token volume and request traffic to this model over time.

Token Consumption

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows

Metrics sourced fromArtificial Analysis

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for. View All

Token Ranking

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