Capability · Comparison
Claude 3.5 Haiku vs Claude 3.5 Sonnet
Claude 3.5 Haiku and Claude 3.5 Sonnet are the fast and capable tiers of the same family — they share instruction-following and safety behaviour but split on capability versus cost. Haiku is the per-token-cheap, low-latency default; Sonnet is the go-to when a task needs real reasoning. Production stacks typically route simple classification and extraction to Haiku and escalate only the hard calls to Sonnet.
Side-by-side
| Criterion | Claude 3.5 Haiku | Claude 3.5 Sonnet |
|---|---|---|
| Context window | 200k tokens | 200k tokens |
| Coding (HumanEval/SWE-bench) | Solid for simple tasks | Strong — near-flagship at release |
| Reasoning depth (MMLU-Pro) | ≈55% | ≈70% |
| Pricing ($/M input) | $0.80 | $3 |
| Pricing ($/M output) | $4 | $15 |
| First-token latency (p50) | Fast | Moderate |
| Tool use | Reliable for single/few tools | Reliable for complex multi-tool loops |
| Vision | Yes | Yes, stronger on detail |
Verdict
Use Haiku by default and escalate to Sonnet only when you actually need the headroom. In measured workloads, 60-80% of requests — classification, summarisation, extraction, simple Q&A — can run on Haiku without a quality regression, while the 20-40% of genuinely hard calls go to Sonnet. That split usually cuts model costs by 3-5x with no user-visible degradation, and it's the cleanest way to budget a mid-scale Claude deployment.
When to choose each
Choose Claude 3.5 Haiku if…
- Task is classification, extraction, routing, or short Q&A.
- Per-token cost is the binding constraint.
- Latency budget is tight (user-facing chat, autocomplete).
- You only need single-turn or shallow tool use.
Choose Claude 3.5 Sonnet if…
- Task needs multi-step reasoning or coding.
- You're running an agent with 5+ tool calls per turn.
- Vision detail matters (charts, technical diagrams).
- A Haiku eval showed quality regressions on your data.
Frequently asked questions
Is Claude 3.5 Haiku good enough for a coding agent?
For a simple assistant that answers questions or suggests snippets, yes. For an agent that plans, edits multiple files, and runs tools, Sonnet or higher is worth the cost.
How do I decide when to escalate from Haiku to Sonnet?
Ship a dual-model eval: run 100-500 real requests through both, score them, and pick the escalation rule (confidence threshold, task type, or complexity heuristic) that gives the best cost-quality ratio.
Are they the same family under the hood?
Same training family, different parameter counts and training mixes. Behaviour and safety are consistent between them, which is what makes routing safe.
Sources
- Anthropic — Models overview — accessed 2026-04-20
- Anthropic — Pricing — accessed 2026-04-20