Llama 3.1 Cheaper Than Mistral Large 3
A recent API pricing comparison shows a significant cost difference between Llama 3.1 8B and Mistral Large 3 for a sample enterprise workload. For a daily task of 100 requests with 1,000 input and 500 output tokens, Llama 3.1 8B would cost approximately $0.81 per month. The same workload on Mistral Large 3 would cost around $3.60 per month.
- Both Llama 3.1 and Mistral Large 2 feature an expanded context window of 128,000 tokens, a significant increase from previous versions. Llama 3.1's context length grew from 8,192 tokens in Llama 3, while Mistral Large 2's predecessor had a 32,000-token window. - Llama 3.1 models are available in 8B, 70B, and a new 405B parameter size, all of which are open-weight. The 405B model is positioned as a competitor to leading proprietary models like GPT-4. Mistral Large 2 has 123 billion parameters and is designed for efficient, single-node inference. - For enterprise adoption, both models are accessible through major cloud platforms including Amazon Bedrock, Microsoft Azure AI Studio, and Google Cloud's Vertex AI. Llama 3.1 also has support from over 25 partners like NVIDIA, Databricks, and Snowflake from its launch. - On performance benchmarks, the larger Llama 3.1 405B model shows a slight edge over Mistral Large in areas like math problem-solving and code generation. However, Mistral Large 2 is noted for its efficiency, achieving comparable or better results than Llama 3.1 on some benchmarks despite having fewer parameters. - From a cost-efficiency perspective, Mistral Large 2 is designed to offer high performance with fewer computational resources. This makes it a strong candidate for applications that require high throughput and where resource constraints are a consideration. - For developers working with inference optimization frameworks, vLLM provides broad support for many Hugging Face models and is known for ease of integration. For maximum performance on NVIDIA GPUs, TensorRT-LLM offers deep optimization but may require more setup effort. - Llama 3.1 has introduced tool-use capabilities, with built-in functions for search and mathematical reasoning via Wolfram Alpha, which can be extended with custom tools. Mistral Large 2 also has enhanced function calling and retrieval skills, allowing it to interact with external systems and APIs. - Both models have expanded their multilingual capabilities. Llama 3.1 supports eight languages including English, German, French, Spanish, Italian, Portuguese, Hindi, and Thai. Mistral Large 2 supports dozens of languages, including several European and Asian languages, and over 80 coding languages.
