Cortecs
Meta has released a new model, Llama 3.3 70B Instruct, now available in GitHub Models. It provides similar performance to Llama 3.1 405B, but at a...
Model details
The Llama 3.3 70B Instruct is an auto-regressive transformer model designed to follow instructions and complete natural language tasks across a wide range of domains. Built as an instruction-tuned variant, it emphasizes conversational and task-oriented interactions, making it well-suited for chatbots, content generation, and language translation applications. The model supports multilingual dialogue across eight languages including English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai, positioning it as a strong choice for global applications. With a 128k context window and grouped query attention, it handles extended conversations and complex multi-turn interactions efficiently. This model achieves benchmark performance comparable to the much larger Llama 3.1 405B parameter version, offering frontier-level results at a more accessible scale.
Training leveraged a new mix of publicly available online data totaling over 15 trillion tokens, and the model was aligned to human preferences through supervised fine-tuning and reinforcement learning with human feedback. This post-training approach helps the model balance helpfulness with safety considerations. The model is ready for commercial deployment, accelerated by TensorRT-LLM for efficient inference on NVIDIA GPUs, and is available for on-demand inferencing, dedicated hosting, and fine-tuning. It outperforms both Llama 3.1 70B and Llama 3.2 90B on text tasks, making it a practical upgrade for organizations already invested in the Llama ecosystem. As an open-weights model, it provides teams with full control for customization and self-hosted deployment.
Transparent token rates
Rates are shown per one million tokens. Combined means one million input plus one million output tokens.
Cortecs
Meta has released a new model, Llama 3.3 70B Instruct, now available in GitHub Models. It provides similar performance to Llama 3.1 405B, but at a...
Cortecs
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). $0 per million input tokens, $0 per million output tokens. 65,536 token context window. Higher uptime with 14 providers. Includes independent benchmarks from Artificial Analysis.
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