By SpiderHunts Technologies · · 8 min read
Choosing a Claude model isn't about picking the "best" one: it's about matching the model to the job. Pay for Opus on a classification task and you waste money; run a complex agent on Haiku and quality suffers. Here's how we pick models when building AI integrations for clients across the USA, UK, Canada, Europe and South Africa.
The three tiers at a glance
Claude Opus 4.8: most capable. The top Opus-tier model: state-of-the-art on complex reasoning, long-horizon agentic work, coding and knowledge tasks. 1M-token context. Roughly $5 input / $25 output per million tokens. Reach for it when correctness matters more than cost.
Claude Sonnet 4.6: best balance. The production workhorse: strong intelligence at materially lower cost and latency than Opus, with a 1M-token context window. Roughly $3 / $15 per million tokens. The right default for most high-volume features.
Claude Haiku 4.5: fastest and cheapest. Built for speed and scale on simpler tasks: classification, routing, short extraction. 200K-token context. Roughly $1 / $5 per million tokens.
(There's also Claude Fable 5, a tier above Opus for the most demanding work, at premium pricing.)
When to use Opus
Complex, multi-step reasoning. Long-horizon agents that plan and execute across many tools. Deep code work and large refactors. High-stakes analysis where a wrong answer is expensive. If the task genuinely stretches a model's intelligence, Opus earns its price.
When to use Sonnet
The bulk of production work: customer-support assistants, summarisation and extraction at volume, RAG over your documents, and most chatbots. Sonnet 4.6 gives you most of Opus's quality at a fraction of the cost and latency: usually the smart default to start with, upgrading to Opus only where evaluation shows it's needed.
When to use Haiku
Speed-critical, simple, high-throughput tasks: classifying tickets, routing requests, tagging content, quick yes/no extraction. Haiku is where you put the millions of cheap calls so you can afford Sonnet and Opus on the ones that matter.
The pro move: route by difficulty
The most cost-effective production systems don't pick one model: they route. Haiku triages and handles the easy cases; Sonnet does the main work; Opus is reserved for the hard ones. Combine that with prompt caching (up to ~90% off repeated context) and batch processing (50% off) and you can run sophisticated AI features at a fraction of the naive cost. We design this routing as part of every build.