概述
Mistral Large 3, Codestral, and Mixtral are distinct releases with different capabilities and terms; check the specific version.
深入探讨
Mistral’s model catalog describes releases and version-specific capabilities. Mistral Large 3 is a multimodal sparse mixture-of-experts model with 41B active and 675B total parameters and Apache 2.0 weights; its documentation supports function calling when an application configures and executes structured tool calls. Codestral 25.08 is a later coding-focused release whose documentation describes code generation and fill-in-the-middle. The 80+ programming-language training and Non-Production License statements apply to the original May 2024 Codestral 22B release, which also describes separate commercial licensing. Mixtral 8x7B is a different sparse MoE release with 13B active of 47B total parameters; its release announcement lists Apache 2.0 weights, and its current model page marks it retired for new integrations. Hosted-service terms are separate from downloadable-weight licenses. A BNP Paribas partnership announcement describes Mistral AI as headquartered in Paris.
现实世界的实施
Model catalog: compare the documented capabilities and terms for Mistral Large 3 and Codestral 25.08.
Research example: Mixtral 8x7B is a sparse mixture-of-experts release; its model page lists 13B active parameters out of 47B total.
Original 2024 Codestral example: the announcement describes a 22B code model trained on 80+ programming languages; later releases require separate checks.
Illustrative: compare a hosted API with self-hosted weights while accounting for separate service, infrastructure, security, and maintenance responsibilities.
Mistral Large 和 Codestral 的未来
Evaluate each model version on the target task and infrastructure, and record the exact checkpoint, license, API configuration, and date checked. Do not generalize performance, availability, or license terms across Mistral’s catalog.
付诸实践
为什么这很重要
- 供应商策略. 供应商路线图会影响您的团队接下来可以构建的功能。
- 成本与预算. 商业条款和部署选项会影响长期成本和风险。
- 风险与安全. 公司激励措施塑造了产品默认、安全态势和开放性。
留意
- 发布公告可能会超过实际生产工作流程的稳定性。
- API 定价或政策转变可能会在一夜之间打破假设。
- 单一供应商依赖性增加了锁定和迁移成本。
后续步骤
- 使用您自己的任务和数据集评估提供商。
- 在集成之前查看隐私、安全和法律条款。
- 维护跨模型或供应商的后备计划。
- 监控发行说明，以便路线图的更改不会让团队感到意外。
不断探索
常见问题
什么是 Mistral Large 和 Codestral？
Mistral AI publishes model releases and hosted services and is headquartered in Paris, according to a BNP Paribas partnership announcement. Mistral Large 3, Codestral, and Mixtral are distinct releases with different capabilities and terms; check the specific version.
Codestral 专门设计用于什么？
Codestral 是 Mistral 的模型，专门用于跨多种编程语言的代码生成、完成和中间填充。
Mistral AI 总部在哪里？
A BNP Paribas press release describes Mistral AI as headquartered in Paris. This location does not imply a market-ranking claim.
Mixtral 使用什么架构来保持高效？
Mistral describes Mixtral 8x7B as a sparse mixture-of-experts model. The architecture claim is specific to that release.
“中间填充”允许 Codestral 做什么？
中间填充让模型在给定的前缀和后缀之间生成代码，这与 IDE 自动完成的工作方式相匹配。
How should developers interpret the licenses of Mistral downloadable weights and hosted services?
Mistral’s May 2024 Codestral 22B announcement describes the Non-Production License and separate commercial licensing; Mixtral 8x7B lists Apache 2.0. Those weight terms are distinct from hosted-service terms, so check the exact model, version, and use.