Claude Haiku 4.5 vs DeepSeek V3.1 Terminus for Translation

What Translation requires: accurate cross-language rendering (multilingual), strict fidelity to source meaning (faithfulness), consistent tone/localization (persona_consistency), reliable JSON/schema output for CAT tools (structured_output), long-context handling for large docs, and sometimes image OCR→translation ability. Our Translation task uses two internal tests: multilingual and faithfulness. External benchmarks are not available for these models (externalBenchmark: null), so our internal taskScore and per-capability scores are primary evidence. In our testing Claude Haiku 4.5: multilingual 5, faithfulness 5, tool_calling 5, long_context 5, persona_consistency 5 — indicating top-tier literal accuracy, glossary/tool integration, and long-document/image workflows. DeepSeek V3.1 Terminus: multilingual 5 but faithfulness 3, structured_output 5, persona_consistency 4, tool_calling 3 — showing it can produce highly formatted outputs and is cost-efficient, but may be less reliable at strict fidelity or complex tool workflows. Use these internal scores to explain why Haiku is the definitive winner for fidelity-sensitive translation and complex input types, while DeepSeek is attractive when structured output and cost are the primary constraints.

1. Scanned product manuals with images and embedded screenshots: Choose Claude Haiku 4.5. Rationale: Haiku’s modality is text+image->text and long_context 5 plus tool_calling 5 in our testing; it handles image-aware localization and long documents that exceed typical token limits. 2) Legal contract translation that must not change meaning: Claude Haiku 4.5. Rationale: faithfulness 5 vs DeepSeek faithfulness 3 in our testing — Haiku is measurably stronger at sticking to source material. 3) Exporting translations into a strict localization JSON schema for a CI pipeline: DeepSeek V3.1 Terminus. Rationale: DeepSeek scores structured_output 5 vs Haiku 4 and is cheaper (output cost per mTok 0.79 vs Haiku 5.00), making it better for high-volume, schema-driven jobs. 4) High-volume, low-margin UI string translation: DeepSeek V3.1 Terminus for cost efficiency (output cost 0.79) if you can tolerate lower faithfulness (3). 5) Multilingual creative marketing copy where tone consistency matters: Claude Haiku 4.5 — persona_consistency 5 vs DeepSeek 4 in our testing, so Haiku better preserves tone and brand voice across languages. All examples reference scores and costs observed in our testing.

For Translation, choose Claude Haiku 4.5 if you need high-fidelity, image-aware, or very long-document translations and can accept higher runtime cost (output cost per mTok 5.00; Haiku is ~6.33× more expensive in our priceRatio). Choose DeepSeek V3.1 Terminus if you need cheaper, text-only translations with excellent structured-output formatting (structured_output 5) and can tolerate lower faithfulness (3) and weaker tool-calling (3). Our recommendations are based on our internal Translation tests (taskScoreA 5 vs taskScoreB 4) and per-capability scores.