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Real human-preference Elo from LMArena blind head-to-head votes. Higher is better; — means not yet ranked in that arena. This is measured, not our estimate.
Blended $/1M across tracked versions of this line.
Typical 3:1 output-to-input mix, per 1M tokens
Price as of 2026-05-10 · Source: anthropic_official_pricing
Mixed text, image, audio and document workloads that benefit from one model across modalities.
Claude Opus 4.5 is Anthropic’s frontier reasoning model optimized for complex software engineering, agentic workflows, and long-horizon computer use. It offers strong multimodal capabilities, competitive performance a...
claude-opus-4.5 is a Multimodal model from Anthropic (US). HotON.ai tracks it at $5.00 per 1M input tokens and $25.00 per 1M output tokens, with a 200K-token context window. Its composite efficiency score is 78/100 at an estimated $0.023 per successful task.
claude-opus-4.5 is tracked at $5.00 per 1M input tokens and $25.00 per 1M output tokens. A typical 3:1 output-to-input workload blends to roughly $20.00 per 1M tokens. Figures are illustrative demo data.
Mixed text, image, audio and document workloads that benefit from one model across modalities.
claude-opus-4.5 supports up to a 200K-token context window — large enough for long documents and extended conversations in a single request.
Within the HotON.ai tracked set, claude-opus-4.5 is cheaper than 5% of models on input price and ranks #515 of 535 by overall efficiency.
Yes — grok-4-fast is a lower-cost option at $0.50 per 1M output tokens, while still covering similar Multimodal use cases. Compare them side by side on HotON.ai.
Ready to paste into articles, papers or AI prompts — prices and date refresh with the live data.
HotON.ai — claude-opus-4.5 (Anthropic): $5.00/1M input, $25.00/1M output, as of 2026-05-10. https://hoton.ai/en/models/anthropic-claude-opus-4-5Pricing is real (via the TestKey catalog, updated daily). Quality (Arena Elo) is real where the model is ranked on LMArena. Efficiency is a modeled composite of real price and context.