Claude Haiku 4.5 vs DeepSeek V3.1 Terminus for Constrained Rewriting

What Constrained Rewriting demands: compression within hard character limits requires preserving key facts while reducing length, strict adherence to length/format constraints, and deterministic, schema-compliant outputs when required. The most important capabilities are: faithfulness (avoiding dropped or invented facts), structured-output compliance (producing exact-length or schema-following text), long-context handling (so truncation doesn’t lose crucial source material), and predictable behavior under low-temperature/regeneration. In our testing both Claude Haiku 4.5 and DeepSeek V3.1 Terminus score 3/5 on the constrained_rewriting test and tie in rank (31 of 52). Supporting metrics explain the split: Haiku scores 5/5 on faithfulness and 5/5 on long_context, indicating strength preserving source facts across long inputs; DeepSeek scores 5/5 on structured_output, showing better strict format and schema compliance. Cost and context-window numbers also matter: Haiku has a 200,000-token window and costs $1 input / $5 output per mTok, while DeepSeek has 163,840 tokens and costs $0.21 input / $0.79 output per mTok. Use the faithfulness and structured_output tradeoff to pick the right model for the specific constrained-rewrite need.

When Claude Haiku 4.5 shines: rewriting a 40k-token technical spec into a 500-character executive summary while preserving accuracy — Haiku’s faithfulness 5/5 and long_context 5/5 reduce risk of omitted or hallucinated facts. When the source includes images that must be condensed to tight caption limits, Haiku’s text+image->text modality and large window are advantageous. When DeepSeek V3.1 Terminus shines: converting freeform product descriptions into exact-length JSON fields or 140-character marketing blurbs at scale — DeepSeek’s structured_output 5/5 enforces schema and length reliably, and its lower cost ($0.21 input / $0.79 output per mTok) makes batching thousands of rewrites economical. Concrete score-driven contrasts from our tests: faithfulness 5 vs 3 (Haiku vs DeepSeek) and structured_output 4 vs 5 (Haiku vs DeepSeek). Both models tie 3/5 on the constrained_rewriting task itself, so these secondary metrics and cost/context specifics determine which model is more practical for your scenario.

For Constrained Rewriting, choose Claude Haiku 4.5 if you must preserve source facts across long inputs, need multimodal (image→text) rewriting, or are prioritizing accuracy (Haiku faithfulness 5 vs 3). Choose DeepSeek V3.1 Terminus if you require strict schema/length compliance and low per-call cost at scale (DeepSeek structured_output 5 vs Haiku 4; costs $0.21/$0.79 vs $1/$5 per mTok). Both score 3/5 on the task and rank identically in our tests; select based on faithfulness and context needs (Haiku) versus structured-output enforcement and price (DeepSeek).