LLM ReferenceLLM Reference

Mixtral Models by MistralAI

MistralAIHighlightOpen Source
5 models2023–2024Up to 64K ctxFrom $0.15/1M 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
Mixtral 8x7B Instruct v0.12023-1233K56BNo

Available From(22 providers)

Pricing

Mixtral model pricing by provider
ModelProviderInput / 1MOutput / 1MType
Mixtral 8x7BMistral AI Studio$0.15$0.45Serverless
Mixtral 8x7B Instruct v0.1DeepInfra$0.15$0.45Serverless
Mixtral 8x7BBitdeer AI$0.18$0.54Serverless
Mixtral 8x7B Instruct v0.1IBM watsonx$0.185$0.185Serverless
Mixtral 8x7BSiliconFlow$0.2$0.2Serverless
Mixtral 8x7BReplicate API$0.2$1Serverless
Mixtral 8x7BMicrosoft Foundry$0.27$0.27Provisioned
Mixtral 8x7BLepton AI API$0.3$0.3Serverless
Mixtral 8x7BGCP Vertex AI$0.4$1.2Serverless
Mixtral 8x7B Instruct v0.1Together AI$0.4$0.4Serverless
Mixtral 8x7B Instruct v0.1OctoML (Deprecated)$0.4$0.6Serverless
Mixtral 8x7BAWS Bedrock$0.45$0.7Serverless
Mixtral 8x7BOctoAI API (Deprecated)$0.45$0.45Serverless
Mixtral 8x7B Instruct v0.1AWS Bedrock$0.45$0.45Serverless
Mixtral 8x7BDatabricks Foundation Model Serving$0.5$1Serverless
Mixtral 8x7BFireworks AI$0.5$0.5Serverless
Mixtral 8x7BDeepInfra$0.54$0.54Serverless
Mixtral 8x7BVultr$0.55$2.75Serverless
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 v0.1OctoAI API (Deprecated)$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 v0.1Microsoft Foundry$2$6Provisioned
Mixtral 8x22B v0.1Mistral AI Studio$2$6Serverless
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

Frequently Asked Questions

What is Mixtral used for?
Mixtral is used for agent workflows and tool use and coding. The family description and listed model capabilities point to those workloads as the best fit.
How does Mixtral compare to Ministral?
Mixtral by MistralAI is strongest where you need agent workflows and tool use, while Ministral by MistralAI is the closest related family to check for structured outputs. Mixtral has 5 listed variants and reaches up to 64K context, while Ministral reaches up to 32K context, so compare the specs and pricing tables before choosing a production model.
Which Mixtral model should I use?
For the lowest listed input price, start with Mixtral 8x7B through Mistral AI Studio at $0.15/1M input tokens. For the most capable/latest local choice, evaluate Mixtral 8x22B Instruct v0.3 with 64K context and function calling.

Models(5)