Mixtral 8x7B

by Mistral AI

8.7

KYI Score

A sparse mixture-of-experts model that matches or outperforms LLaMA 2 70B while being faster and more efficient through its innovative architecture.

LLMApache 2.0FREE46.7B (8x7B MoE)

Official Website Hugging Face

Quick Facts

Model Size: 46.7B (8x7B MoE)
Context Length: 32K tokens
Release Date: Dec 2023
License: Apache 2.0
Provider: Mistral AI
KYI Score: 8.7/10

Best For

→Code generation

→Multilingual tasks

→Reasoning

→Content creation

Performance Metrics

Speed

8/10

Quality

8/10

Cost Efficiency

9/10

Specifications

Parameters: 46.7B (8x7B MoE)
Context Length: 32K tokens
License: Apache 2.0
Pricing: free
Release Date: December 11, 2023
Category: llm

Key Features

Mixture of ExpertsFast inferenceMultilingualFunction calling

Pros & Cons

Pros

✓Excellent speed-quality balance
✓Efficient architecture
✓Strong multilingual
✓Apache 2.0 license

Cons

!Smaller context than LLaMA 3.1
!Complex architecture

Ideal Use Cases

Code generation

Multilingual tasks

Reasoning

Content creation

Mixtral 8x7B FAQ

What is Mixtral 8x7B best used for?

Mixtral 8x7B excels at Code generation, Multilingual tasks, Reasoning. Excellent speed-quality balance, making it ideal for production applications requiring llm capabilities.

How does Mixtral 8x7B compare to other models?

Mixtral 8x7B has a KYI score of 8.7/10, with 46.7B (8x7B MoE) parameters. It offers excellent speed-quality balance and efficient architecture. Check our comparison pages for detailed benchmarks.

What are the system requirements for Mixtral 8x7B?

Mixtral 8x7B with 46.7B (8x7B MoE) requires appropriate GPU memory. Smaller quantized versions can run on consumer hardware, while full precision models need enterprise GPUs. Context length is 32K tokens.

Is Mixtral 8x7B free to use?

Yes, Mixtral 8x7B is free and licensed under Apache 2.0. You can deploy it on your own infrastructure without usage fees or API costs, giving you full control over your AI deployment.

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