In a significant leap forward in the development of the Large Language Model (LLM), Mistral AI announced the release of its newest model, Mixtral-8x7B.
magnet:?xt=urn:btih:5546272da9065eddeb6fcd7ffddeef5b75be79a7&dn=mixtral-8x7b-32kseqlen&tr=udp%3A%2F%https://t.co/uV4WVdtpwZ%3A6969%2Fannounce&tr=http%3A%2F%https://t.co/g0m9cEUz0T%3A80%2Fannounce
Release a6bbd9affe0c2725c1b7410d66833e24
— Mistral AI (@MistralAI) December 8, 2023
What is Mixtral-8x7B?
Mixtral-8x7B by Mistral AI is a Mixture of Experts (MoE) model designed to improve the way machines understand and generate text.
Think of it as a team of specialized experts, each specializing in a different area, working together to manage different types of information and tasks.
a report published June reportedly shed light on the intricacies of OpenAI’s GPT-4, noting that it uses a similar approach to MoE, using 16 experts, each with about 111 billion parameters, and routing two experts per pass to optimize costs.
This approach allows the model to handle diverse and complex data efficiently, making it useful for creating content, engaging in conversations, or translating languages.
Performance metrics of Mixtral-8x7B
The new Mistral AI model, Mixtral-8x7B, represents a significant step forward from its previous version, Mistral-7B-v0.1.
It is designed to better understand and create text, a key feature for anyone looking to use AI for writing or communication tasks.
This latest addition to the Mistral family promises to revolutionize the AI landscape with its improved performance metrics, as shared by OpenCompass.
What makes Mixtral-8x7B stand out is not only its improvement over the previous version of Mistral AI, but the way it stacks up against models like Llama2-70B and Qwen-72B.
It’s like having an assistant who can understand complex ideas and express them clearly.
One of the key strengths of the Mixtral-8x7B is its ability to handle specialized tasks.
For example, it performed exceptionally well on specific tests designed to evaluate AI models, indicating that it is good at general text comprehension and generation and excels in more niche areas.
This makes it a valuable tool for marketers and SEO experts who need AI that adapts to different content and technical requirements.
The Mixtral-8x7B’s ability to tackle complex math and coding problems also suggests it can be a useful ally for those working on more technical aspects of SEO, where understanding and solving algorithmic challenges is crucial.
This new model could become a versatile and intelligent partner for a wide range of strategic and digital content needs.
How to test Mixtral-8x7B: 4 demos
You can experiment with Mistral AI’s new model, Mixtral-8x7B, to see how it responds to queries and how it performs against other open source models and OpenAI’s GPT-4.
Please note that, like all generative AI content, platforms running this new model may produce inaccurate information or unintended results.
User feedback on new models like this will help companies like Mistral AI improve future releases and models.
1. Perplexity Labs Playground
In Perplexity laboratoriesyou can try Mixtral-8x7B along with the new online LLMs of Meta AI Llama 2, Mistral-7b and Perplexity.
In this example, I query for the model itself and notice that new instructions are added after the initial response to expand the content generated about my query.
Screenshot from Perplexity, December 2023
Even though the answer seems correct, it starts to repeat itself.
Screenshot from Perplexity Labs, December 2023
The model provided a 600+ word answer to the question “What is SEO?”
Again, additional instructions appear as “headers” to apparently ensure a complete response.
Screenshot from Perplexity Labs, December 2023
2. Poem
Poe hosts bots for popular LLMs, including OpenAI’s GPT-4 and DALL·E 3, Meta AI’s Llama 2 and Code Llama, Google’s PaLM 2, Anthropic’s Claude-instant and Claude 2, and StableDiffusionXL.
These bots cover a wide spectrum of capabilities, including text, image, and code generation.
The Mixtral-8x7B-Chat bot is powered by Fireworks AI.
Poe screenshot, December 2023
It is worth saying that the fireworks page specifies that it is an “unofficial implementation” that has been tweaked for chat.
When asked what are the best backlinks for SEO, he provided a valid answer.
Poe screenshot, December 2023
Compare this with the answer powered by Google Bard.
Screenshot from Google Bard, December 2023
3. Vercel
Vercel offers a demonstration of Mixtral-8x7B that allows users to compare responses from popular Anthropic, Cohere, Meta AI, and OpenAI models.
Screenshot from Vercel, December 2023
It provides an interesting perspective on how each model interprets and responds to user questions.
Screenshot from Vercel, December 2023
Like many LLMs, he occasionally hallucinates.
Screenshot from Vercel, December 2023
4. Replicate
The mixtral-8x7b-32 demonstration where Replica is based on this source code. It is also noted in the README that “Inference is quite inefficient”.
Screenshot from Replicate, December 2023
In the example above, Mixtral-8x7B is described as a game.
conclusion
The latest version of Mistral AI sets a new benchmark in the field of AI, offering improved performance and versatility. But like many LLMs, it can provide inaccurate and unexpected answers.
As AI continues to evolve, models like the Mixtral-8x7B could become integral to setting up advanced AI tools for marketing and business.
Featured image: T. Schneider/Shutterstock
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