Claude Haiku 4.5 vs Claude Opus 4.6 for Agentic Planning

What Agentic Planning demands: goal decomposition, step sequencing, tool selection, structured outputs for execution, long context handling, and safe refusal or recovery when plans fail. In our testing both models achieve 5/5 on agentic_planning (tied for 1st among 52 models), and both hit 5/5 on tool_calling, long_context, and faithfulness — all critical for plan execution. The deciding strengths are safety_calibration and creative_problem_solving: Opus scores 5 vs Haiku's 2 on safety_calibration (better at refusing or gating risky actions in our tests) and 5 vs 4 on creative_problem_solving (generating non‑obvious recovery strategies). Operational differences also matter: Opus has a 1,000,000 token context window and 128,000 max output tokens versus Haiku's 200,000/64,000, and Opus supports an extra parameter ('verbosity') useful for agent control. There is no external benchmark for this task in the payload, so our internal 1–5 scores are the primary evidence.

Where Claude Opus 4.6 shines: orchestrating a multi‑step automation that must avoid unsafe API calls (safety_calibration 5 vs 2), recovering from partial failures by inventing alternate subplans (creative_problem_solving 5 vs 4), and running agents over extremely long histories or multi‑document workflows (context window 1,000,000; max_output_tokens 128,000). Where Claude Haiku 4.5 shines: high‑throughput planning tasks that need the same 5/5 agentic reasoning and tool calling but at much lower cost and latency (input/output cost per mTok: 1/5 for Haiku vs 5/25 for Opus), or prototypes where budget and response time matter more than the top safety calibration. Shared strengths: both scored 5/5 on tool_calling, long_context, and agentic_planning in our tests, and both support structured_outputs and the core tool parameters for building agents.

For Agentic Planning, choose Claude Haiku 4.5 if you need top-tier agentic reasoning at minimal cost and latency (input/output cost per mTok: 1/5) and can accept weaker safety calibration. Choose Claude Opus 4.6 if you require stronger safety calibration (5 vs 2 in our tests), better creative failure recovery (5 vs 4), larger context (1,000,000 tokens) and are willing to pay higher costs (input/output cost per mTok: 5/25).