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shashank ms
shashank ms

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Using LLM for Machine Translation: An Oxlo Perspective

Machine translation has moved beyond rigid phrase-based and neural systems. Modern large language models capture nuance, idioms, and domain-specific terminology through in-context learning, making them viable production engines for multilingual pipelines. Oxlo.ai offers a developer-first inference platform that supports this shift with request-based pricing and a broad catalog of multilingual models, including Qwen 3 32B and Llama 3.3 70B, accessible via a fully OpenAI-compatible API.

Why LLMs for Translation

Traditional neural machine translation (NMT) models map source to target text through dedicated encoder-decoder architectures. LLMs generalize this capability inside a chat/completions interface. They accept natural language instructions, handle few-shot examples, and adapt

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