In a move towards advancing artificial intelligence, Mistral AI, a pioneer in delivering cutting-edge open models, has unveiled Mixtral 8x7B. This high-quality sparse mixture-of-experts (SMoE) model with open weights marks a significant leap in the field. Steering away from conventional architectures and training paradigms, Mistral AI aims to empower the developer community with original models, fostering innovation and diverse applications.

Mixtral 8x7B Overview

Mixtral 8x7B emerges as a decoder-only model, leveraging a sparse mixture-of-experts network. With a set of 8 distinct parameter groups, the feedforward block dynamically selects two experts at each layer to process tokens, combining their outputs additively. This innovative approach boosts the model’s parameter count to 46.7B while maintaining cost and latency control, operating at the speed and cost efficiency of a 12.9B model.

Pushing the Frontier with Sparse Architectures

Mistral AI pioneers the use of sparse architectures with Mixtral, demonstrating a commitment to pushing the boundaries of open models. The router network in Mixtral efficiently processes input data, selecting specific groups of parameters per token. This strategic utilization of parameters enhances performance without compromising speed or cost, making Mixtral a formidable contender in the AI landscape.

Performance Metrics

Mixtral is put to the test against Llama 2 models and the GPT3.5 base model. The results showcase Mixtral’s prowess, outperforming Llama 2 70B and matching or surpassing GPT3.5 across various benchmarks. The quality versus inference budget tradeoff graph illustrates the efficiency of Mixtral 8x7B, placing it among highly efficient models compared to Llama 2 counterparts.

Hallucination, Biases, and Language Mastery

A critical analysis of Mixtral’s performance reveals its strengths in TruthfulQA, BBQ, and BOLD benchmarks. In comparison to Llama 2, Mixtral exhibits higher truthfulness and reduced bias. The model showcases proficiency in multiple languages, including French, German, Spanish, Italian, and English.

Also Read: From GPT to Mistral-7B: The Exciting Leap Forward in AI Conversations

Our Say

Mistral AI’s Mixtral 8x7B not only sets a new standard for open models but also addresses ethical considerations. By actively identifying and measuring hallucinations, biases, and sentiment, Mistral AI demonstrates a commitment to refining the model through fine-tuning and preference modeling. The release of Mixtral 8x7B Instruct further emphasizes Mistral AI’s dedication to providing a versatile, high-performing, and ethical open-source model.