Claude Haiku vs Sonnet: When to Use Each Model

In the Claude Haiku vs Sonnet decision, Haiku 4.5 ($1/$5 per million tokens) is the fast, cheap choice for classification, extraction, and high-volume work, while Sonnet 5 ($3/$15) costs three times more but reasons far better for coding, writing, and multi-step analysis. Default to Sonnet, and drop to Haiku when speed and price outweigh depth.

Prices and specs verified 31 July 2026 against Anthropic's model overview.

We route real production traffic across both tiers every day on this site, so this isn't abstract for us — it sets our monthly bill and our response times. The debate reduces to a single trade-off: raw throughput against reasoning depth. Below is the speed gap, the price gap, the quality gap, the context-window difference, and a decision guide you can apply per task rather than per project. For the full lineup, our pillar guide to every Claude model sets the wider context.

Claude Haiku vs Sonnet at a glance

Haiku is one-third the price with one-fifth the context. That's the whole trade in one line.

Sonnet 4.6 remains available at the same $3/$15 for teams pinned to it, but Sonnet 5 costs the same at standard rates and less during the introductory window, so new projects have no reason to start on 4.6. The practical choice is almost always Haiku versus a Sonnet — not one Sonnet versus another.

The throughput gap

Haiku runs roughly 3× faster on simple prompts and 4–5× faster on typical production workloads, returning short responses in under 200 milliseconds.

Anthropic positions Haiku 4.5 as near-frontier intelligence at a fraction of the latency and cost, and in our own pipelines the difference is obvious the moment volume climbs.

Latency is multiplicative at scale, which is why the gap matters far more than it looks on a single call. A tagging job over a million records that takes 800 milliseconds each on Sonnet drops to well under 300 milliseconds on Haiku — that is hours saved across the batch, not seconds. For real-time chat, autocomplete, content moderation, and anything a user actively waits on, that throughput is the difference between an interface that feels instant and one that stalls.

Cost: the cheapest Claude model

$1/$5 against $3/$15 — exactly one-third, on both input and output. An identical workload costs a Sonnet three times what Haiku charges.

Because the ratio is clean on both streams, the math never needs a calculator. Here is a concrete example, processing 10 million input tokens and generating 2 million output tokens:

That $40 difference is trivial on one request and decisive across millions. During the introductory window the gap narrows to 2×, but once standard pricing resumes it returns to a flat 3×. For the complete rate card, including batch and prompt-caching discounts, see our Claude API pricing guide.

Is Sonnet better for coding and reasoning?

Yes — but only on reasoning-heavy work. On classification, extraction, and routing, Haiku stays within a few points, because those tasks never exercise the gap.

Sonnet reasons through multi-step problems, holds far more of a codebase in working memory, catches subtle logic errors, and follows long instructions that Haiku tends to flatten. On any benchmark stressing multi-step reasoning, maths, or code understanding, Sonnet pulls clearly ahead — and the gap widens as the task gets harder.

That single insight is the whole game: match the model to whether the real bottleneck is depth or throughput.

Context windows and when 1M tokens matters

If a task must reason over more than roughly 150,000 tokens at once, the choice is already made — it's Sonnet, regardless of speed or price.

Haiku 4.5 has a 200,000-token context window; Sonnet 5 offers 1,000,000 — five times larger. For short prompts the difference is invisible. But feed a model an entire repository, a book-length document, or a long multi-turn agent transcript, and Haiku runs out of room exactly where Sonnet keeps going. Context size alone can settle the decision before any other factor.

When to use each

Haiku for anything high-volume, latency-sensitive, and well-specified. Sonnet when quality is the constraint.

Send to Haiku 4.5: classification, tagging, extraction, formatting, routing, summarization, and real-time chat or support. These are the jobs where the speed and one-third price win outright, and where accuracy sits within a rounding error of Sonnet's.

Reach for Sonnet 5 when quality is the constraint: coding beyond small snippets, large-codebase work, subtle debugging, long-form writing, multi-step analysis, and agents that chain many tool calls. Here the reasoning depth is genuinely worth paying 3× for, because a wrong answer costs more than the token difference ever will. The honest default is Sonnet first, with Haiku as the deliberate optimisation once you have measured a task and know it is safe to drop down.

A decision guide

Decide per task, not per project. Many teams route each request automatically based on its complexity.

If you're comparing Claude against other assistants entirely, or want to know what Claude costs across plans, those guides go a level up. And when even Sonnet's reasoning falls short on the hardest refactors or research, that's the moment to read Claude Sonnet vs Opus — the next escalation up the ladder.

The quick version:

• Haiku 4.5 costs $1/$5 per MTok; Sonnet 5 costs $3/$15
• Haiku is fastest; Sonnet is stronger on nuance
• Haiku holds 200K tokens; Sonnet holds 1M
• Volume work leans Haiku; quality work leans Sonnet

On a batch of 10,000 support tickets to classify, Haiku finishes for roughly a third of Sonnet's cost — and on a task that simple, the accuracy gap is invisible.

Claude pricing at a glance

Both tiers are bundled into the same subscriptions, so the Haiku-versus-Sonnet cost difference only shows up on the API.

For the full breakdown of every plan, see our how much Claude costs guide.