There isn’t one universally “best” multilingual LLM for cross-language search, but for a global SaaS search stack the strongest default choices are usually:

Best overall for multilingual retrieval

intfloat/multilingual-e5-large or BAAI/bge-m3
These are often better picks than a pure chat LLM for search because they’re built for embeddings / retrieval, which is what cross-language search usually needs.

Why these stand out

• Strong cross-lingual semantic matching
• Good performance across many languages
• Suitable for:
  • query → document retrieval
  • semantic search
  • multilingual RAG
• Faster and cheaper than using a generative LLM for every search request

If you specifically need a generative multilingual LLM

Top options:

• OpenAI GPT-4o / GPT-4.1
• Claude 3.5 Sonnet
• Gemini 1.5 Pro

These are excellent for:

• query rewriting
• multilingual query understanding
• answer synthesis
• translating/search assistance

But for search relevance itself, embeddings + reranking usually outperform “LLM-only” search.

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Recommended architecture for a global SaaS product

1) Use a multilingual embedding model

A strong default:

• BAAI/bge-m3
  Good multilingual coverage, flexible, strong retrieval quality.

Alternative:

• multilingual-e5-large Also very strong and widely used.

2) Add a multilingual reranker

Rerankers can dramatically improve precision for search results:

• bge-reranker-v2-m3
  or another multilingual cross-encoder reranker.

3) Use an LLM only where it adds value

Use a strong multilingual LLM for:

• translating user queries when needed
• query normalization
• intent detection
• answer generation over retrieved results
• handling ambiguous searches

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Practical recommendation

If you want one “best” stack for a SaaS product:

Best balance of quality + scalability

• Embeddings: BAAI/bge-m3
• Reranker: bge-reranker-v2-m3
• LLM: GPT-4o or Claude 3.5 Sonnet for query understanding and response generation

If you want a very simple starting point

• Embeddings: intfloat/multilingual-e5-large
• LLM: GPT-4o

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Decision guide

Choose based on your needs:

• Lowest latency / self-hosted / open source:
  bge-m3 + bge-reranker-v2-m3

• Best managed API quality:
  GPT-4o or Claude 3.5 Sonnet, but still pair with embeddings for retrieval

• Best multilingual search relevance:
  Multilingual embeddings + reranker, not just an LLM

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If you want, I can give you:

1. a top-3 model shortlist by budget,
2. a reference architecture for multilingual SaaS search, or
3. a benchmarking plan to evaluate models on your own data.