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claude-haiku-4-5 — pricing, context window and limits

The previous Haiku, still served at one price for any prompt length, and the only current model with a 200K context window and a 64K output cap. The effort parameter errors here, and its 4096-token cache minimum means short prompts silently will not cache. It still accepts prefill and the older budget_tokens thinking, both of which Haiku 5.5 rejects.

Price per million tokens

Input$1
Output$5
Cache write, 5-minute TTL$1.25
Cache write, 1-hour TTL$2
Cache read$0.10 (0.1x input)
Batch input / output$0.50 / $2.50

Limits and behaviour

StatusCurrent
Context window200K tokens
Max output64K tokens
Min cacheable prefix4,096 tokens
Effort levelsnot supported
Effort default—
ThinkingFixed budget_tokens, off unless requested
Forced tool_choiceAccepted
PlatformsClaude API, Amazon Bedrock, Google Cloud, Microsoft Foundry

Lifecycle

API model nameclaude-haiku-4-5-20251001
Retires no sooner than15 Oct 2026
SuccessorClaude Haiku 5.5

The previous Haiku, still served

Haiku 5.5 has replaced this model as the current Haiku, at a lower per-token price. Haiku 4.5 is still served, and it is still the only current model with the smaller context window and output cap the table above shows. What it keeps over its successor is predictability: one price at any prompt length, and a request surface that still accepts prefill, sampling parameters and fixed thinking budgets — all of which Haiku 5.5 rejects. See migrating: Haiku 4.5 to Haiku 5.5 before you move.

No effort parameter — the one to check for in shared code

Unlike every other current model in the main lineup, the effort parameter errors outright here rather than being accepted or ignored. Request-building code shared across a model fleet needs to branch on this specifically. See the effort parameter errors on Haiku 4.5 for exactly this failure. Thinking, where you want it, still uses the older fixed-budget form.

A cache minimum that catches short prompts

This model's minimum cacheable prefix is among the highest in the lineup, so a short prompt that caches cleanly on the newest models can silently fail to cache here, with no error to flag it. The combination of a low per-token rate and the highest bar to clear before caching applies is the detail most likely to make this model underperform its price on paper.

Watch its lifecycle row

Among current models, this is the one whose earliest possible retirement date comes soonest, as the lifecycle table above shows. That floor is not a retirement — Anthropic announces one with notice — but a high-volume pipeline pinned to this id should know where its fallback would go.

See Claude Haiku 5.5 for its successor, Sonnet 5.5 vs Haiku 4.5 for what the step up buys, and Claude model retirement dates for the full calendar.

Verified 2026-10-28 against claude-api skill — shared/models.md, model-migration.md + SKILL.md model table and Anthropic's pricing and model-deprecation pages (canonical: https://platform.claude.com/docs/en/about-claude/models/overview, https://platform.claude.com/docs/en/about-claude/pricing, https://platform.claude.com/docs/en/about-claude/model-deprecations).

Verified 2026-10-28 against Anthropic's model-deprecations status table and pricing page (canonical: https://platform.claude.com/docs/en/about-claude/model-deprecations, https://platform.claude.com/docs/en/about-claude/pricing).Could not confirm: These dates apply to the Claude API, Claude Platform on AWS, Claude Models on Google Cloud (Anthropic managed) and Microsoft Foundry. Amazon Bedrock and Claude Models on Google Cloud (Google managed) keep their own retirement schedules, which we do not track.