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Claude Haiku 4.5

The fastest Claude with near-frontier intelligence.

4.3Released October 2025Haiku tier · lowest latency

Overview

Claude Haiku 4.5 is the speed-and-cost tier of the Claude family — the fastest model Anthropic ships, with surprisingly strong intelligence for its price. It's built for high-volume, latency-sensitive work: classification, routing, extraction, real-time chat and the cheap-but-frequent steps inside larger agent pipelines.

What makes Haiku notable is how little you give up. In blind tests it occasionally produces the cleanest, most constraint-faithful output of the entire Claude lineup on short tasks, proving that the smallest model can win when the job rewards concision over deliberation. For anything that runs thousands of times a day, Haiku is the obvious starting point.

Key capabilities

  • Lowest latency in the Claude family
  • Near-frontier quality on short tasks
  • Ideal for high-volume, real-time workloads
  • Cheapest Claude pricing

At a glance

Latency

Fastest (Claude)

Price

Lowest Claude tier

Pricing: Cheapest Claude tier — built for volume.

Pros & cons

What we like

  • Extremely fast and cheap
  • Punches above its weight on short tasks
  • Great for agent sub-steps and routing

Trade-offs

  • Weaker on long, complex reasoning
  • Not a substitute for Opus/Sonnet on hard work

The verdict

4.3Aggregate review

Claude Haiku 4.5 proves the smallest model can still win. For real-time chat, high-volume pipelines and the cheap inner steps of agents, it delivers near-frontier quality at a fraction of the cost — just don't ask it to carry your hardest reasoning.

Best for: High-volume, low-latency tasks and agent sub-steps.

Frequently asked questions

What is Claude Haiku 4.5 best at?

Fast, cheap, high-volume work — classification, extraction, routing and real-time chat — plus the inexpensive inner steps of larger agent workflows.

Can Haiku replace Sonnet?

For short, well-scoped tasks it often can. For long or complex reasoning, step up to Sonnet or Opus.

Further reading

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