Claude Haiku 4.5 vs Claude Opus 4.6 for Multilingual

Multilingual demands equivalent quality across languages: idiomatic translation, terminology preservation, consistent tone, and robust handling of long or mixed-language context. The primary signal in our suite is the 'multilingual' test; both models achieve a top score of 5/5 and are tied for 1st in our testing. Supporting signals that matter for multilingual workflows include faithfulness (both 5), persona_consistency (both 5), long_context (both 5) and structured_output (both 4). Differences that affect real deployments: Opus 4.6 has a far larger context window (1,000,000 tokens vs Haiku's 200,000) and higher max output tokens (128,000 vs 64,000), which helps when processing very large multilingual documents in one pass. Haiku 4.5 is substantially cheaper (input/output mTok: 1/5) compared with Opus (5/25), making it better for high-volume localization. Also note divergent safety and classification scores in our tests: Opus scores 5 on safety_calibration vs Haiku's 2, while Haiku scores 4 on classification vs Opus's 3 — these secondary differences can influence which model you pick depending on compliance and routing needs.

1. High-volume website localization (cost-sensitive): Haiku 4.5 is better. Both models scored 5/5 for Multilingual in our tests, but Haiku's output cost is 5 per mTok vs Opus 25, so Haiku gives equal quality at ~1/5 the output spend. 2) Large manual-translation-of-archive (huge context): Opus 4.6 is better. Opus supports a 1,000,000-token context window and 128,000 max output tokens vs Haiku's 200,000/64,000, enabling single-pass processing of long multilingual documents. 3) Regulated content and safe refusals across languages: Opus 4.6 is preferable because it scored 5 on safety_calibration in our testing compared with Haiku's 2, lowering risk for moderation-critical multilingual AI tasks. 4) Intent classification and routing in non-English inputs: Haiku 4.5 has a classification score of 4 vs Opus's 3 in our tests, so Haiku may be marginally better for language-based routing at lower cost. 5) Agentic, multi-step multilingual workflows: both models tied at 5 for agentic_planning and tool_calling, but Opus's larger context and higher safety score favor complex, long-running pipelines despite higher cost.

For Multilingual, choose Claude Haiku 4.5 if you need top-tier non-English output at the best cost — it matches Opus 4.6's 5/5 quality in our tests and costs 5× less per output mTok. Choose Claude Opus 4.6 if you must process extremely large multilingual contexts in a single pass or need stronger safety calibration for regulated or moderation-sensitive multilingual content.