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Claude Haiku vs Sonnet for batch workloads
Focused on classification, extraction, and RAG preprocessing — not creative chat. Pick by $/1k rows and label quality on your CSV.
Quick comparison
| Model | Best for | Context / out | Cost posture |
|---|---|---|---|
| Haiku 4.5 | Proven high-throughput jobs | 200K / 64K | Prior-gen Haiku list |
| Haiku 5.5 | Next-gen bulk labeling & routing | 1M / 128K | $0.10 / $0.50 ≤100K prompt |
| Sonnet 5.5 | Reasoning, coding, long analysis | Large / heavier | ~$2 / $10 list — usually overkill for tags |
When to pick Haiku 5.5
- Thousands of short rows (reviews, tickets, chunks)
- Latency and cost matter more than deep reasoning
- You need larger context than Haiku 4.5 allowed
- You can follow Haiku 5.5 API rules (no temperature; adaptive thinking)
When to keep Sonnet
Multi-step policy judgment, coding-style transforms, or rows where a wrong label is expensive. Using Sonnet for every trivial sentiment tag inflates spend — compare list rates on Claude Haiku pricing.
Migration checklist (4.5 → 5.5)
- Remove temperature / top_p / top_k from requests.
- Recount tokens (newer tokenizer ≈ +30%).
- Raise max_tokens if thinking is on.
- Handle refusal stop reasons.
- Re-run a golden CSV before flipping production.
BatchHaiku is an independent third-party tool, NOT affiliated with or endorsed by Anthropic. Live inference runs Claude Haiku 5.5 via Cloudflare AI under your account usage terms.
Related guides
- Claude Haiku pricing (4.5 & 5.5)
List rates, long-context tiers, and cost per 1k CSV rows.
- Claude Haiku 5.5 benchmarks
AA Index, Terminal-Bench, SWE — with sources cited.
- Haiku 5.5 vs GPT-6 Luna
Same short-tier price — different long-context thresholds & scores.
- Claude Haiku batch API & CSV jobs
Classify / extract at scale — BatchHaiku’s product wedge.
- Live model comparison tool
Switch Haiku, Luna, Sonnet, Opus side by side on the homepage.