Claude Haiku 4.5 vs R1 0528 for Constrained Rewriting

Constrained Rewriting demands accurate compression into strict character limits while preserving meaning and required content. Key capabilities: faithfulness (staying true to source), predictable structured output when schemas are required, ability to compress without dropping mandatory elements, and stable behavior under tight token budgets. In our testing the primary signal is the constrained_rewriting benchmark score (no external benchmark supplied). Supporting evidence: both models have top-tier faithfulness (5) and long_context (5), meaning they both can retain source fidelity and handle long inputs. Differences that explain R1 0528's win: a higher constrained_rewriting score (4 vs 3) and stronger safety_calibration (4 vs 2) in our tests. Operational factors matter too: Claude Haiku 4.5 offers a larger context window (200,000 tokens) and explicit multimodal support (text+image->text), while R1 0528's quirks require higher max completion tokens to avoid empty outputs on short tasks. Output cost and token behavior also affect real-world throughput and batching costs (see practical examples).

1. High-volume UI text compression (batch subtitle or UI strings): R1 0528 shines — scored 4 vs 3, and its output cost is $2.15/mTok versus Claude Haiku 4.5 at $5/mTok, lowering per-output expense when compressing many strings. Ensure you set high max completion tokens to avoid empty responses from R1 0528's 'empty_on_structured_output/constrained_rewriting' quirk. 2) One-off, long-source compressions (novel chapter summaries with strict char limits): Claude Haiku 4.5 is preferable if you want a predictable out-of-the-box run because it has a larger context window (200,000 tokens) and does not carry R1 0528's empty-response quirk; expect a lower constrained_rewriting score in our tests (3 vs 4) but fewer runtime adjustments. 3) Safety-sensitive compression (redacting or compressing user content where refusal calibration matters): R1 0528 scored better on safety_calibration (4 vs 2), so in our testing it handled harmful/edge requests with more conservative calibration while still achieving higher constrained_rewriting scores. 4) Structured output pipelines: both models score 4 on structured_output in our tests, but R1 0528 lists an operational note that it returns empty responses on structured_output unless configured correctly — plan for that in automated pipelines.

For Constrained Rewriting, choose R1 0528 if you need the better constrained_rewriting score in our tests (4 vs 3), lower output cost ($2.15 vs $5 per mTok), and stronger safety calibration, and you can set high max completion tokens to avoid empty responses. Choose Claude Haiku 4.5 if you need a larger context window (200,000 tokens), multimodal text+image->text input support, or prefer fewer runtime tweaks for guaranteed non-empty outputs despite the lower constrained_rewriting score.