Mixtral 8x7B Instruct v0.1

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Mixtral 8x7B Instruct, licensed under Apache 2.0, is a powerful language model with a large context window. It's great at simulated dialogues and general language understanding, making it perfect for customer service chatbots and interactive storytelling. However, it might struggle with more specialized tasks.

Context window(in thousands)32768

Use cases for Mixtral 8x7B Instruct v0.1

  1. Multilingual content generation: Mixtral 8x7B Instruct v0.1 excels at generating high-quality text in multiple languages, ideal for global communication and content creation.
  2. Advanced conversational agent: With a high Arena Elo rating and the ability to handle complex prompts, it’s perfect for developing advanced chatbots or virtual assistants that offer human-like interactions.
  3. Educational tools: Its ability to generate human-like text and follow instructional prompts makes it great for creating interactive educational content, tutoring systems, or study guides.
Arena Elo1114
MT Bench8.3

Mixtral 8x7B Instruct v0.1 exhibits exceptional performance in Arena Elo and MMLU, indicating high-quality responses and strong reasoning abilities. Its excellent MT Bench score shows its proficiency in translation.

Llama 3 Instruct (8B)


GPT-3.5 Turbo-0613


Mixtral 8x7B Instruct v0.1


GPT-3.5 Turbo


GPT-3.5 Turbo-0125


Throughput(output tokens per second)96
Latency(seconds to first tokens chunk received)0.33
Total Response Time(seconds to output 100 tokens)1.6

This model offers high throughput and low latency, making it ideal for high-volume applications. However, it might not be the best for situations needing ultra-low response times.


The cost per 1,000 tokens for running the model with Telnyx Inference is $0.0003. For instance, analyzing 1,000,000 customer chats, assuming each chat is 1,000 tokens long, would cost $300.

What's Twitter saying?

  • In RAG pipelines: Tuana shows how to integrate Mixtral-8x7B-Instruct-v0.1 by MistralAI with Haystack_AI in Colab. Users can customize the pipeline, modify prompts, and explore functionalities on the web. (Source: Tuana's tweet)
  • WebUI for Mixtral 8x7b: Andrew Zhu suggests Mixtral 8x7B as a practical replacement for GPT-4 in daily tasks, sharing a link for more information. (Source: Andrew Zhu's tweet)
  • Performance: Mark L. Watson notes that Mixtral-8x7B-Instruct-v0.1-q2 outperforms Mistral:7b-instruct-q4 in RAG tasks, based on his experiments with personal documents. (Source: Mark L. Watson's tweet)

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What is Mixtral-8x7B-instruct-v0.1?

Mixtral-8x7B-instruct-v0.1 is a version of the Mixtral-8x7B large language model developed by Mistral AI, optimized for instruction following through supervised fine-tuning and direct preference optimization (DPO). It supports multilingual content, uses a sparse Mixture of Experts (MoE) architecture for efficiency, and is designed for high performance in tasks requiring careful instruction following.

How does Mixtral-8x7B-instruct-v0.1 compare to GPT-3.5 and other models?

Mixtral-8x7B-instruct-v0.1 outperforms GPT-3.5 on most benchmarks, offering 6x faster inference speeds. It surpasses other open-source models like Llama 2 70B in terms of performance and efficiency, making it a top choice for instruction-based tasks.

What languages does Mixtral-8x7B-instruct-v0.1 support?

This model supports five languages: English, French, Italian, German, and Spanish. This multilingual capability makes it suitable for a wide range of text generation and processing applications in these languages.

What makes Mixtral-8x7B-instruct-v0.1 efficient?

The model's sparse Mixture of Experts (MoE) architecture, which activates only a small number of specialized sub-models (experts) based on the input, makes it highly efficient. Despite its 45 billion parameters, it only uses 12.9 billion parameters per token, enhancing both performance and computational efficiency.

What is the context window size of Mixtral-8x7B-instruct-v0.1?

The context window of Mixtral-8x7B-instruct-v0.1 is 32,000 tokens, allowing it to handle longer input sequences effectively compared to many other models.

Under what license is Mixtral-8x7B-instruct-v0.1 released?

Mixtral-8x7B-instruct-v0.1 is released under the Apache 2.0 license, which is one of the most permissive and open licenses available, facilitating its use in both commercial and non-commercial projects.

How can I integrate Mixtral-8x7B-instruct-v0.1 into my app?

You can integrate Mixtral-8x7B-instruct-v0.1 into your connectivity apps via platforms like Telnyx. For more information on getting started, visit Telnyx's developer documentation.

What are some practical applications of Mixtral-8x7B-instruct-v0.1?

Mixtral-8x7B-instruct-v0.1 excels in tasks that require careful instruction following, such as generating text based on specific prompts or guidelines. Its multilingual support and computational efficiency also make it suitable for a wide range of applications in text generation and processing across various languages.