Compare Llama 3.3 70B Instruct (Free) and MiniMax M3 on key metrics including price, context length, throughput, and other model features.
The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction-tuned generative model with 70B parameters. Optimized for multilingual dialogue, it outperforms many open-source and closed chat models on industry benchmarks. Supported languages include English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.
MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding, and tool use. It is built on MiniMax Sparse Attention (MSA), which replaces full attention with KV-block selection to cut per-token compute at long context — roughly 1/20 the cost of the previous generation at 1M tokens, with substantially faster prefill and decode while retaining quality across most tasks. Trained as a native multimodal model on interleaved data and tuned for multi-turn, production-like collaboration via an interactive user-simulator framework, the model is oriented toward sustained, multi-step tasks rather than single-turn execution.