Claude Haiku 4.5 vs Claude Opus 4.6 for Long Context

Long Context demands reliable retrieval and reasoning across 30K+ tokens, stable persona and faithfulness when referencing distant context, durable tool-calling for multi-step workflows, and the ability to emit large, structured outputs without truncation. On our tests both Claude Haiku 4.5 and Claude Opus 4.6 hit 5/5 for long_context and tie for rank 1, and both score 5/5 on tool_calling and 5/5 on faithfulness — indicating comparable core retrieval accuracy in isolation. Opus 4.6 adds practical advantages for long-running, production workflows: a 1,000,000-token context_window and max_output_tokens 128,000 (vs Haiku 200,000 / 64,000), plus a safety_calibration score of 5 (Haiku is 2). Additionally, Opus 4.6 reports SWE-bench Verified 78.7% and AIME 2025 94.4% (Epoch AI), which are useful external signals for robustness on coding and structured reasoning workloads; Claude Haiku 4.5 has no external benchmark entries in the payload. Structured_output is equal (4/5) for both, so format adherence is comparable; cost and capacity are the decisive factors.

1. Large legal or financial corpus extraction: Choose Claude Opus 4.6 — 1,000,000-token window and 128,000 max output let you ingest multiple long contracts, extract clause-level references, and produce consolidated exhibits without splitting documents. Safety_calibration 5 reduces risk when handling sensitive or borderline content. 2) Low-latency enterprise summaries and iterative editing: Choose Claude Haiku 4.5 — same long_context score (5/5) and strong tool_calling (5/5) let you perform multi-document summarization up to 200,000 tokens at far lower cost (input 1/output 5 per mTok vs Opus input 5/output 25 per mTok). 3) Agent-driven, workflow-wide automation: Prefer Opus 4.6 when your agent must maintain state across many tasks and emit long machine-readable outputs; its larger window and higher safety score give operational headroom. 4) Ad-hoc research or chat over a long document: Haiku 4.5 is cost-efficient for exploratory passes where the 200K window is sufficient. Concrete numbers: context_window — Haiku 200,000 vs Opus 1,000,000; max_output_tokens — Haiku 64,000 vs Opus 128,000; costs — Haiku input 1 / output 5 per mTok, Opus input 5 / output 25 per mTok. Also note Opus's external results: 78.7% on SWE-bench Verified and 94.4% on AIME 2025 (Epoch AI) as supplementary evidence of robustness.

For Long Context, choose Claude Haiku 4.5 if you need lower-cost, lower-latency processing for large-but-not-maximal contexts (up to 200,000 tokens) or many quick passes where cost per mTok matters. Choose Claude Opus 4.6 if you require maximum context capacity (1,000,000 tokens), larger single-call outputs (128,000 tokens), stronger safety calibration (5 vs 2), and the operational reliability those factors buy — and you can accept higher input/output costs (Opus input 5/output 25 per mTok vs Haiku input 1/output 5 per mTok).