Model comparison · 2026-09-23
Claude Haiku 4.5: the first stop for classification, support, and summarization before Opus
Covers that anthropic/claude-haiku-4.5's catalog description calls itself 'a budget-friendly first stop before stepping up to Sonnet or Opus,' and which tasks that first stop is sufficient for.
The catalog description defines its own role
anthropic/claude-haiku-4.5's catalog description positions itself directly: it works well for classification, support flows, summarization, and quick assistant scenarios, and is a budget-friendly first stop before stepping up to Sonnet or Opus. That shows Haiku isn't a 'weak Claude' — it's a model deliberately optimized for a specific task class.
On price ($1/$5 per million tokens), it's a fifth of Claude Opus 5's ($5/$25) and a quarter of Opus 5.5's ($4/$20), the current model in the Opus line. It also supports function calling, image input, and document input, so the base interface you use on Opus 5 is there on Haiku too.
Which tasks this first stop is sufficient for
For tasks like categorizing a customer support ticket, summarizing an email, classifying a text's sentiment, or producing a quick standard reply to a user question, complex multi-step reasoning isn't needed; on these tasks, Haiku 4.5's speed and low cost outweigh a more capable, slower model's payoff.
Most of these tasks are high-volume (a request per support ticket, per incoming email); a low unit price is the main factor determining total cost at that volume. When task complexity rises (a multi-step analysis, a task needing a nuanced decision), Haiku's quality ceiling can fall short; at that point, stepping up to Sonnet, and to Opus if needed, is the natural path the catalog description suggests.
- Classification, categorization, short summarization: Haiku 4.5 is usually enough.
- High-volume, repetitive tasks: the low unit price determines total cost.
- Multi-step tasks needing a nuanced decision: consider stepping up to Sonnet or Opus.
A routing layer gains on both ends
In a mixed task distribution (mostly simple classification, occasionally complex analysis), an architecture that first evaluates the incoming request against a simple rule or a lightweight classifier, routing simple tasks to Haiku and complex ones to Sonnet/Opus, optimizes total cost by using the right model on both ends.
Frequently asked questions
Does Haiku 4.5 carry all of Opus 5's capabilities?
The base interface (function calling, image input, document input) is the same, but Opus 5's advanced capabilities like adaptive thinking and an extended reasoning_effort range aren't on Haiku; the catalog description positions Haiku for simpler tasks.
When should I start directly with Opus instead of trying Haiku?
If the task genuinely needs complex, multi-step reasoning or a long-context agent loop from the start, starting directly with Opus can save time versus starting with Haiku and upgrading later; for simple tasks, starting with Haiku lowers cost.