Claude Haiku: Anthropic's Fast, Low-Cost Line

Redaktion ·

What Claude Haiku stands for

Haiku is the bottom of the three classic Claude lines — and the only one where speed and price are the first selection criterion, not the second. Since Claude 3, Anthropic has split its models into three sizes: Opus for the hardest work, Sonnet as the balanced middle, Haiku for everything that has to happen fast and in large numbers. What’s striking is how far the bar has moved: on many tasks Haiku 4.5 reaches the level that marked the Sonnet class a year earlier — at a fraction of the cost.

One thing to keep straight: Haiku deliberately lags in the version cycle. While Sonnet, Opus and the new Fable tier are already on generation 5, Haiku 4.5 from October 2025 remains the current model of the line as of September 2026.

Suitability profile: Claude Haiku (flagship)
CodingReasoningTextVisionSpeedKosten-Eff.
  • Coding 3.5 / 5 · Claude Opus 5 u. a.
  • Reasoning 3 / 5 · Claude Opus 5 u. a.
  • Text 4 / 5 · Claude Fable 5.1
  • Vision 3.5 / 5 · Gemini 3.1 Pro
  • Speed 5 / 5 · Feld-Spitze
  • Kosten-Eff. 4.5 / 5 · GPT Luna u. a.

Eignung 0–5 · redaktionelle Einordnung, kein Benchmark · gestrichelt = Feld-Bestwert je Achse

The profile is the mirror image of Opus: top marks on speed and cost efficiency, solid on text and coding, deliberately restrained on deep reasoning. That’s exactly what the line is built for.

Where it fits

Haiku earns its keep on tasks that demand high volume and low latency:

  • Classification and extraction — routing tickets, pulling entities from documents, filling structured fields, thousands of times a day.
  • Real-time chat support — short response times are a feature here, not just nice to have.
  • Fast parallel sub-agent — under an orchestrating Sonnet or Opus, working through the many small sub-steps at the same time. This pattern is exactly what makes Haiku valuable in multi-agent systems.

How to choose: Haiku, Sonnet or Opus?

The three lines solve the same underlying problem at different points on the curve of capability, speed and price. The positioning map shows where Haiku stands in the field:

Positioning: Haiku in the field
Frontier Allrounder Volumen Geschwindigkeit / Kosten-Effizienz → Fähigkeit / Reasoning ↑ Claude Opus 5 Gemini 3.8 Flash Claude Haiku 4.5 GPT Luna

Redaktionelle Einordnung, kein Benchmark

As a rule of thumb:

  • Latency and price are the bottleneck, the task is clearly scoped? Then Haiku.
  • You want good quality at moderate volume? Then Sonnet.
  • A long run where every intermediate step has to land? Then Opus.

Against Google’s Gemini Flash or GPT Luna, Haiku occupies the same volume zone: fast, cheap, moderate reasoning depth. Gemini Flash adds native video and audio, Luna trails Haiku slightly on coding. Which model fits is decided by the concrete modality of your task.

Read on

FAQ

What sets Claude Haiku apart from Sonnet and Opus?
Its place in the line architecture: Haiku is tuned for low latency and low cost, Sonnet is the balanced mid-tier, Opus the top-tier line for the hardest reasoning and coding work.
Does Claude Haiku 4.5 support the effort parameter?
No. No model in the Haiku line supports effort levels; Anthropic's model spec explicitly lists "Default effort: Not supported" for Haiku 4.5. Reasoning depth runs instead through a manual, numeric thinking budget (budget_tokens).
What is Claude Haiku best suited for?
Tasks with high volume and low latency — classification, extraction, chat support — as well as a fast parallel sub-agent in multi-agent systems under an orchestrating Sonnet or Opus.
Is there a Claude Haiku 5 yet?
As of September 2026, no. Haiku 4.5 from October 2025 remains the current flagship of the line, even though Sonnet, Opus and the new Fable/Mythos tier are already on generation 5.
How does Haiku compare to Gemini Flash or GPT Luna?
All three occupy the same volume zone: fast, cheap, moderate reasoning depth. Gemini Flash adds native video and audio, GPT Luna trails Haiku slightly on coding score.
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