LLM Reference

Mixtral

MistralAIHighlightOpen Source
5 models2023–2024Up to 64K ctxFrom $0.18/1M input

About

The Mixtral family of large language models (LLMs), developed by Mistral AI, offers a groundbreaking approach in open-source AI through a sparse mixture-of-experts (SMoE) architecture. This innovative design allows the models to manage a significant number of parameters while ensuring efficient inference speed by activating only a subset of parameters for each token. Such architecture enables Mixtral models to deliver performance on par with much larger models, standing out in various benchmarks and outperforming competitors like Llama 2, and even equaling the prowess of closed-source models such as GPT-3.5. These models are multilingual, supporting languages such as English, French, Italian, German, and Spanish, and excel in domains like code generation. Instruction-tuned versions like Mixtral-8x7B-Instruct-v0.1 cater to applications requiring robust instruction-following and chat capabilities. The Mixtral family provides versatile models of differing sizes, addressing diverse computational and application requirements.

Specifications(5 models)

Mixtral model specifications comparison
ModelReleasedContextParametersFn Calling
Mixtral 8x22B Instruct v0.32024-0764K8x22BYes
Mixtral 8x22B v0.12024-0464K8x22BNo
Mixtral 8x22B Instruct v0.12024-0464K8x22BNo
Mixtral 8x7B2023-1232K8x7BNo
Vultr Mixtral 8x7B2023-123276847000000000No

Available From(20 providers)

Pricing

Mixtral model pricing by provider
ModelProviderInput / 1MOutput / 1MType
Mixtral 8x7BBitdeer AI$0.18$0.54Serverless
Mixtral 8x7BSiliconFlow$0.2$0.2Serverless
Mixtral 8x7BReplicate API$0.2$1Serverless
Mixtral 8x7BAzure OpenAI$0.27$0.27Provisioned
Mixtral 8x7BLepton AI API$0.3$0.3Serverless
Mixtral 8x7BAWS Bedrock$0.45$0.7Serverless
Mixtral 8x7BOctoAI API$0.45$0.45Serverless
Mixtral 8x7BMistral AI Studio$0.45$0.7Serverless
Mixtral 8x7BDatabricks Foundation Model Serving$0.5$1Serverless
Mixtral 8x7BFireworks AI$0.5$0.5Serverless
Mixtral 8x7BPerplexity Labs$0.6$0.6Serverless
Mixtral 8x7BIBM watsonx$0.6$0.6Serverless
Mixtral 8x22B v0.1DeepInfra$0.65$0.65Serverless
Mixtral 8x22B Instruct v0.1SiliconFlow$0.65$0.65Serverless
Mixtral 8x22B v0.1Mistral AI Studio$0.9$0.9Serverless
Mixtral 8x22B v0.1OctoAI API$1.2$1.2Serverless
Mixtral 8x22B v0.1Fireworks AI$1.2$1.2Serverless
Mixtral 8x22B v0.1Together AI$1.2$1.2Serverless
Mixtral 8x22B Instruct v0.1Fireworks AI$1.2$1.2Serverless
Mixtral 8x22B v0.1Azure OpenAI$2$6Provisioned
Mixtral 8x22B Instruct v0.1OpenRouter$2$6Serverless
Mixtral 8x22B Instruct v0.3Replicate API$2$2Serverless
Mixtral 8x22B Instruct v0.1Replicate API$2.1$2.1Serverless
Mixtral 8x7BDeepInfra$54$54Serverless

Frequently Asked Questions

What is Mixtral?
The Mixtral family of large language models (LLMs), developed by Mistral AI, offers a groundbreaking approach in open-source AI through a sparse mixture-of-experts (SMoE) architecture. This innovative design allows the models to manage a significant number of parameters while ensuring efficient inference speed by activating only a subset of parameters for each token. Such architecture enables Mixtral models to deliver performance on par with much larger models, standing out in various benchmarks and outperforming competitors like Llama 2, and even equaling the prowess of closed-source models such as GPT-3.5. These models are multilingual, supporting languages such as English, French, Italian, German, and Spanish, and excel in domains like code generation. Instruction-tuned versions like Mixtral-8x7B-Instruct-v0.1 cater to applications requiring robust instruction-following and chat capabilities. The Mixtral family provides versatile models of differing sizes, addressing diverse computational and application requirements.
How many models are in the Mixtral family?
The Mixtral family contains 5 models.
What is the latest Mixtral model?
The latest model is Mixtral 8x22B Instruct v0.3, released in 2024-07.
How much does Mixtral cost?
Mixtral models range from $0.18/1M to $54/1M input tokens depending on the model and provider.

Models(5)