Llama 3.3 70b Instruct

Llama 3.3 70B Instruct carries forward Meta's open-weight strategy with a focus on multilingual conversational applications. This 70 billion parameter model is pretrained and instruction-tuned, designed to excel in dialogue use cases where fluency across multiple languages matters. The model supports eight languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, with a generous 131,072 token context window that enables extended multi-turn conversations and complex reasoning across language boundaries. Its architecture builds on the proven Llama foundation while adding optimizations specifically for instruction-following and conversational coherence.

Benchmark evidence shows the model delivers meaningful improvements over its predecessors, with Oracle's documentation noting it surpasses both Llama 3.1 70B and Llama 3.2 90B on text-based tasks. The instruction-tuned variant is available for fine-tuning, giving enterprises and developers a pathway to customize the base model for domain-specific applications. FlashAttention-4 support enables efficient inference on modern hardware, making the model practical for production deployments. Together AI lists it among models excelling in dialogue scenarios, positioning it as a strong choice for applications requiring natural multilingual conversation at scale.