Claude Haiku 4.5 vs Claude Sonnet 4.6 for Structured Output

Structured Output (JSON schema compliance and format adherence) demands strict format fidelity, deterministic key ordering where required, faithful omission of extraneous fields, and stable handling of nested schemas and long payloads. In our testing both models score 4/5 on the structured_output test and share rank 26 of 52, so their baseline schema compliance is equivalent. Supporting capabilities that matter here are: tool_calling (both 5/5 in our tests) for invoking validators or formatters, faithfulness (both 5/5) to avoid hallucinated fields, and long_context (both 5/5) when schema plus data exceed short windows. Sonnet's advantages in safety_calibration (5 vs 2) reduce risky acceptance of malformed or unsafe schema requests, and its larger context/output limits and stronger creative_problem_solving help when the task requires iterative schema construction, large exports, or merging many examples into one output. Cost and latency are also structuring constraints: Haiku is materially cheaper (input 1, output 5 per mTok) compared with Sonnet (input 3, output 15 per mTok), which influences production choices even when functional parity exists.

1. Large export / nested schema: Produce a single JSON document representing 500 records with nested arrays and footnotes. Sonnet 4.6 is preferable because it supports up to 128,000 output tokens and a 1,000,000-token context window, reducing the need to chunk or stitch outputs. 2) High-assurance API responses: If outputs are used in downstream systems where safety and exact schema adherence are critical (financial PII routing, automated ingestion), Sonnet's safety_calibration 5 vs Haiku's 2 provides greater built-in refusal/permit discrimination in our tests. 3) Low-cost, high-throughput: For routine schema-conformant payloads of moderate size where latency and cost dominate (webhooks, small payload exports), Claude Haiku 4.5 gives the same 4/5 structured_output score at lower per-mTok cost (input 1, output 5 vs Sonnet input 3, output 15), and matches Sonnet on tool_calling and faithfulness. 4) Iterative schema design: For generating and refining complex schemas from examples, Sonnet's creative_problem_solving 5 vs Haiku 4 helps when the model must propose non-obvious but feasible field structures while keeping to JSON constraints.

For Structured Output, choose Claude Haiku 4.5 if cost, latency, or efficiency matter for moderate-size schemas and you need solid schema compliance at lower per-mTok rates (input 1 / output 5). Choose Claude Sonnet 4.6 if you need stronger safety guarantees, higher creative/problem-solving when designing schemas, or support for very large contexts and outputs (1,000,000 vs 200,000 token context; 128,000 vs 64,000 max output tokens) and are willing to pay more (input 3 / output 15).