Claude Haiku 4.5 vs R1 0528 for Structured Output

Structured Output (JSON schema compliance and format adherence) demands: strict response_format/structured_outputs support, predictable token budgeting (no unexpected empty outputs), enough max_output_tokens to emit large schemas, long-context handling when schemas are embedded in long prompts, and faithfulness to input constraints. In our testing both models score 4/5 on the structured_output benchmark and occupy the same task rank (26 of 52). Supporting metrics matter: tool_calling (both 5/5) helps with argument selection and sequencing when composing structured payloads; faithfulness (both 5/5) supports staying within schema rules; safety_calibration differs (Claude Haiku 4.5 = 2/5, R1 0528 = 4/5) which can matter when schema output must omit sensitive content. Crucially, R1 0528's quirks show it “returns empty responses on structured_output” and “uses reasoning tokens that consume output budget,” plus it requires high max completion tokens — all practical failure modes for schema adherence. Where these quirks matter, the internal parity in structured_output score does not translate to equal reliability.

1. API response generator (small-to-medium JSON payloads): Claude Haiku 4.5 — reliable. It supports structured_outputs/response_format, large max_output_tokens (64k), and a 200k context window, producing non-empty, schema-compliant JSON in our runs. R1 0528 — risky: same 4/5 score but the model can return empty structured_output responses in our tests, causing downstream failures. 2) Large schema + long instructions (embedded in long context): Claude Haiku 4.5 — better due to 200k context window and explicit structured_outputs support. R1 0528 has a 163,840 context window but may consume reasoning tokens and require high min_max_completion_tokens, increasing cost and the chance of truncated or empty results. 3) Safety-constrained structured outputs (omit or redact fields flagged as sensitive): R1 0528 — preferable on safety calibration (R1 4/5 vs Haiku 2/5), so it may better refuse or redact disallowed content per policy rules. 4) Size-constrained format-compression (tight character limits): R1 0528 edges Haiku on constrained_rewriting (R1 4/5 vs Haiku 3/5), so where exact compression within hard limits is required, R1 can be advantageous if you can avoid its empty-output quirk. 5) Cost-sensitive batch generation: R1 0528 is cheaper (input 0.5¢/mTok, output 2.15¢/mTok) versus Claude Haiku 4.5 (input 1¢/mTok, output 5¢/mTok), but cost savings are irrelevant if R1 returns empty structured outputs and triggers retries.

For Structured Output, choose Claude Haiku 4.5 if you need dependable, schema-compliant JSON with large context and reliable non-empty responses. Choose R1 0528 if lower per-token cost, better safety calibration, or slightly stronger constrained_rewriting matter AND you can tolerate or work around R1 0528’s documented empty_response behavior on structured_output (or only use it in contexts where that quirk is absent).