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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteChoose Claude Haiku 5.5 when you need low-latency, lower-cost responses across many clearly defined requests—such as classification, extraction, routing, summarization, or live support—and can verify that its answers meet your quality bar. Choose Sonnet 5.5 for well-scoped work that needs a stronger balance of speed and capability, and Opus 5.5 when complex coding or knowledge work warrants the higher-capability tier. These are Anthropic’s recommendations, not guarantees for every workload; test representative examples before routing production traffic.
When Haiku is the better fit
Anthropic describes Haiku 5.5 as the fastest model in its current Claude line and recommends it when speed and volume matter most. It is a strong starting point for tasks that are repeated, narrowly specified, and straightforward to evaluate.
- Classification, extraction, and routing: Label incoming text, pull defined fields, or direct requests to the appropriate workflow.
- Summaries and text generation: Produce bounded outputs where the expected format and relevant information can be checked.
- Real-time interaction: Consider Haiku for chat, voice, live support, or other experiences where response time matters.
- Repetitive computer use and subagent work: Use it for focused, repeatable browser or desktop actions, or as a subagent for a limited part of a larger workflow.
- Simple coding: It may suit focused coding tasks; do not assume that makes it the right choice for complex software engineering.
These examples come from Anthropic’s Haiku guidance. They identify plausible use cases, not a guarantee that Haiku will meet your accuracy requirements on every input.
When to choose Sonnet or Opus instead
A larger model is worth considering when a task’s reasoning demands, ambiguity, or error costs outweigh the savings from using Haiku. Anthropic positions Sonnet 5.5 as a fit for well-scoped work needing a balance of speed and intelligence, and Opus 5.5 for complex coding and knowledge work.
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|---|---|---|
| Haiku 5.5 | High-volume, clearly scoped requests, including classification, routing, summaries, real-time assistants, repetitive computer use, subagents, and simple coding. | Fastest |
| Sonnet 5.5 | Well-scoped tasks where a balance of speed and capability is wanted. | Fast |
| Opus 5.5 | Complex coding and knowledge work. | Moderate |
The use cases and relative latency labels reflect Anthropic’s model guidance; they are not latency guarantees for a particular application. Your actual response time and output quality depend on your workload and deployment.
Compare token costs using your prompt size
Anthropic’s published API rates, accessed October 7, 2026, show a substantial price difference for prompts up to 100K tokens. Prices below are per million tokens, with input and output listed separately.
| Model and prompt tier | Input | Output |
|---|---|---|
| Haiku 5.5, up to 100K tokens | $0.10 | $0.50 |
| Haiku 5.5, over 100K tokens | $0.50 | $2.50 |
| Sonnet 5.5, up to 100K tokens | $2 | $10 |
| Opus 5.5, up to 100K tokens | $4 | $20 |
These are Anthropic’s listed rates for the stated tiers, not a universal quote for every access route. Check the current pricing page and the relevant provider’s terms if using a cloud-hosted route such as Amazon Bedrock or Google Cloud. Rates and availability can change.
To estimate a request’s token cost, multiply its input tokens by the input rate and its output tokens by the output rate, then add the results. Use your actual prompt-size distribution: a Haiku prompt over 100K tokens has a different listed rate from one at or below that threshold. Also account for the service route you use.
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- Describe the workload. Record request volume, typical and unusually large prompt sizes, latency target, expected output, and the cost of a wrong answer.
- Start with Haiku for bounded, high-volume work. Use it as the initial candidate for latency-sensitive tasks that match Anthropic’s documented examples.
- Evaluate against a larger model where it matters. Run representative inputs through Haiku and Sonnet or Opus when reasoning is complex or mistakes carry meaningful costs. Check both output quality and response time against your requirements.
- Estimate cost by token tier and access route. Apply the current input and output rates to your observed token usage, including prompts above 100K tokens, and verify any cloud-provider pricing that applies.
- Escalate uncertain cases if your evaluation calls for it. A fallback to a larger model can be an implementation option when Haiku misses your quality target. Treat that as a design choice to validate, not as a routing architecture prescribed by Anthropic.
Check the model version before implementing
Anthropic’s lifecycle documentation lists Haiku 5.5 and Haiku 4.5 as active, while Haiku 3 and Haiku 3.5 are retired; the page names Haiku 4.5 as their replacement. Verify the current model IDs and status in Anthropic’s model lifecycle documentation before building or updating API instructions, because model names and availability can change.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Keep version-specific claims attached to the version
Anthropic’s Haiku page calls Haiku 5.5 “The cheapest, fastest, and most capable small model we’ve ever released.” That is the company’s positioning, not an independent comparative finding. A separate figure sometimes relevant to coding discussions belongs to an older release: Anthropic reported 73.3% on SWE-bench Verified for Haiku 4.5 in its October 15, 2025 announcement. It is a vendor-published benchmark claim about Haiku 4.5, not a result for Haiku 5.5.
Sources: Anthropic Haiku page; Anthropic pricing; Anthropic model lifecycle documentation.
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