概览
主要功能
- 高级推理和指令遵循
- 内置多语种支持
- 代码生成和调试
- 函数调用和 JSON 输出
- 长语料处理
- 企业部署选项
价格
- 模型
- Free
- 分类
- 微为架的给布系统
- 评分
- 4.7 / 5 (6)
使用场景
文档理解
睿风 Large 24.11可以分析和理解文档、图表和自然图像，同时保持领导水平的文本only理解.
数学推理
该模型在复杂的数学推理上获得69.4%的成绩，超过所有其他模型，在视觉数据上进行数学推理。
多语言 OCR 和推理
睿风 Large 24.11可以进行多语言 OCR 和推理任务，如计算订单中包括小费的总金额.
优点 & 缺点
优点
- 支持多语种任务的强大性能
- 坚实的编码和数学推理能力
- 支持函数调用和结构化输出
- 可通过 API 和主要云提供商使用
缺点
- 闭源权重商业模型
- API 使用费在高规模下快速增加
- 不适合简单任务的规模和速度
对决战绩
在万神殿中参与了 1 对决。
Last battle
评测
6 个评分的平均值。
登录以留下评测。
Compared a few options
Evaluated this against two competitors. Where it wins: code generation and debugging and available via API and major cloud providers. On balance the feature set — especially advanced reasoning and instruction following — justifies the 5 stars for our use case.
Compared a few options
Evaluated this against two competitors. Where it wins: native multilingual support and available via API and major cloud providers. Where it lags: aPI usage costs can scale quickly at high volume. On balance the feature set — especially native multilingual support — justifies the 5 stars for our use case.
Compared a few options
Evaluated this against two competitors. Where it wins: enterprise deployment options and solid coding and math reasoning capabilities. On balance the feature set — especially native multilingual support — justifies the 5 stars for our use case.
Does the job
Pretty happy overall. Function calling and JSON outputs just works and supports function calling and structured outputs. API usage costs can scale quickly at high volume can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.
Does the job
Pretty happy overall. Code generation and debugging just works and solid coding and math reasoning capabilities. Closed-weights commercial model can be annoying, but no dealbreakers — I'd recommend it to a friend without hesitating.
Years in this space
I've evaluated a lot of these over the years. What stands out here is advanced reasoning and instruction following — handled better than most — and strong multilingual performance across major languages. Not the smallest or fastest option for simple tasks is my one real gripe. Worth the time if this is your use case.
问答
Is Mistral Large 24.11 suitable for multilingual applications and long‑context tasks?
The model offers native multilingual support across major languages and a long‑context window, enabling reliable reasoning in chatbots, document analysis, and retrieval‑augmented applications that involve extended text or multilingual inputs.
Asked by Ekaterina Orlova · Jan 18, 2026
Can Mistral Large 24.11 handle structured outputs like JSON for function calling?
Yes, the model natively supports function calling and can emit structured JSON outputs, making it suitable for workflows that require precise data formats such as automated code generation or API orchestration.
Asked by Halime Yalcin · Jan 6, 2026
Which cloud platforms provide Mistral Large 24.11 and how can I integrate it into my existing stack?
The model is accessible through Mistral’s own API and also via major partner cloud providers. Integration can be done using standard REST or SDK calls, allowing you to embed it in applications, data pipelines, or serverless functions.
Asked by Celeste Marchetti · Jan 3, 2026
What pricing model does Mistral Large 24.11 use and how does cost scale with usage?
Mistral Large 24.11 is offered via a commercial API, so usage is billed per request or token. Costs increase with higher request volumes, and the model’s large size means it can become expensive for high‑throughput workloads.
Asked by Zelda Brandt · Nov 16, 2025
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