Mixtral Models by MistralAI

MistralAIApache 2.0Open sourceHighlightOpen Source
MistralAI releases · 25 in the last 12 monthsChangelog →
5 models2023–2024Up to 64K ctxFrom $0.150/1M input

Last refreshed 2026-10-06. Next refresh: weekly.

Details

ResearcherMistralAI
LicenseApache 2.0OSI-approved
Commercial usePermitted
Models5
Released2023–2024
Max context64K

Capabilities

JSON / Tool use1 of 5 models

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.

Decision facts

Best fit
JSON / Tool usecoding
Capability starting point
Mixtral 8x22B Instruct v0.1 with 64K context
Lowest tracked input
Mixtral 8x7B · $0.150/1M · Mistral AI Studio
Closest related family
Agents-A1

Current Variants

Use-when guidance is based on each model's tracked capabilities, context window, release date, and replacement status.

5 in view

Use when the workload needs 64K context and JSON / Tool use.

2024-0764K contextJSON / Tool use

Use when the workload needs 64K context.

2024-0464K context

Use when the workload needs 64K context.

2024-0464K context

Use when the workload needs 32K context.

2023-1232K context

Use when the workload needs 32K context and 56B parameters.

2023-1232K context56B parameters

Release Timeline

3 release groups
2024-07
1 current
Mixtral 8x22B Instruct v0.3
64K contextJSON / Tool use
Current
2024-04
2 current
Current
Current
2023-12
2 current
Mixtral 8x7B
32K context
Current
Mixtral 8x7B Instruct v0.1
32K context56B parameters
Current

Specifications(5 models)

Mixtral model specifications comparison
ModelReleasedContextParametersJSON / Tool use
Mixtral 8x22B Instruct v0.32024-0764K8x22BYes
Mixtral 8x22B Instruct v0.12024-0464K8x22BNo
Mixtral 8x22B v0.12024-0464K8x22BNo
Mixtral 8x7B2023-1232K8x7BNo
Mixtral 8x7B Instruct v0.12023-1232K56BNo

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 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 8x7B Instruct v0.1AWS Bedrock$0.45$0.7Serverless
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 8x22B v0.1DeepInfra$0.65$0.65Serverless
Mixtral 8x22B Instruct v0.1SiliconFlow$0.65$0.65Serverless
Mixtral 8x22B v0.1Together AI$1.2$1.2Serverless
Mixtral 8x22B Instruct v0.1Fireworks AI$1.2$1.2Serverless
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

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