This model is deprecated. We only continue performance benchmarking for the default 10k input token workload. Results for other workloads are historical and no longer updated.

Mistral has launched a newer release, Mistral Medium 3.5. We suggest considering it instead.

Mistral

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Proprietary model

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Released 2025年8月

Mistral Medium 3.1 智能、性能与价格分析

立即试用 API 服务商基准测试

智能Updated

Artificial Analysis Intelligence Index

速度

无

每秒输出 token 数

成本

输入 US$0.00输出 US$0.00

无

Intelligence Index 每项任务的成本

冗长度

18M

Intelligence Index 输出 token 数

Mistral Medium 3.1 的智能水平高于平均水平，价格也很有竞争力；比较对象为其他价格相近的非推理模型。该模型支持文本和图像输入，可输出文本，上下文窗口为 128k 个 token。

Mistral Medium 3.1 在 Artificial Analysis Intelligence Index 上的得分为 9，在同类模型中高于平均水平（中位数：7）。在 Intelligence Index 评测中，它生成了 18M 个 token；与 12M 的中位数相比，其回答有些冗长。

Mistral Medium 3.1 每 100 万输入 token 的价格为 $0.00（很有竞争力，中位数：$0.05），每 100 万输出 token 的价格为 $0.00（很有竞争力，中位数：$0.15）。

推理	否此页面展示该模型的非推理版本。可能还存在推理版本。
输入模态	支持：文本和图像
输出模态	支持：文本
上下文窗口	128k 约 192 页 A4 纸（12 号 Arial 字体）

指标与同类别模型进行比较：

非推理模型 → 仅与其他非推理模型比较
推理模型 → 同时与推理和非推理模型比较
开放权重模型 → 仅与规模类别相同的其他开放权重模型比较：

微型：≤4B 个参数
小型：4B–40B 个参数
中型：40B–150B 个参数
大型：>150B 个参数

专有模型 → 与价格区间相同的专有模型和开放权重模型比较，采用输入/输出价格 3:1 的混合比例：

每 100 万 token <$0.15
每 100 万 token $0.15–$1
每 100 万 token >$1

亮点

Updated

智能

Artificial Analysis Intelligence Index · Higher is better

速度

Output tokens per second · Higher is better

每任务成本

Weighted average cost (USD) per Intelligence Index task · Lower is better

智能Updated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1

Artificial Analysis Intelligence Index v4.3.2 includes: AA-Briefcase v1.1, GDPval-AA v2.1, AutomationBench-AA, Terminal-Bench 4.0, SciCode, Humanity's Last Exam, GDP.pdf, CritPt, AA-Omniscience, AA-LCR v1.1. See Intelligence Index methodology for further details, including a breakdown of each evaluation and how we run them.

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Indicates whether the model weights are available. Models are labelled as 'Commercial Use Restricted' if commercial use is limited by conditions, and as 'Non-commercial' if the license prohibits commercial use.

能力指数

衡量模型在特定能力和行业中的表现

Artificial Analysis Finance & Accounting Index

Incorporates 7 evaluations: AA-Omniscience, GDPval-AA v2.1, AA-Briefcase v1.1, Humanity's Last Exam, AutomationBench-AA, AA-LCR v1.1, GDP.pdf · Higher is better

基准测试

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

AA-Briefcase v1.1Updated

Agentic knowledge work, (Elo-500)/2000

GDPval-AA v2.1Updated

Agentic real-world work tasks, (Elo-500)/2000

AutomationBench-AAUpdated

Agentic SaaS workflows

Terminal-Bench 4.0New

Agentic coding & terminal use

SciCode

Coding

Humanity's Last Exam

Reasoning & knowledge

GDP.pdfNew

Professional document reasoning, All-pass

CritPtUnder review

Physics reasoning

AA-Omniscience Accuracy

Knowledge

AA-Omniscience Non-Hallucination Rate

1 - hallucination rate

AA-LCR v1.1

Long context reasoning

Harvey LAB-AA

Legal agentic work, criterion pass rate

EnterpriseOps-Gym-AA

Agentic business operations

Terminal-Bench-Science 0.1New

Agentic scientific research workflows in a terminal

AA-AnalystAgent

Quantitative analysis on spreadsheets & documents

𝜏³-Banking

Agentic tool use

ITBench-AA

Kubernetes incident root-cause analysis

MMMU-Pro

Visual reasoning

MLCR-AA

Medical long context reasoning

While model intelligence generally translates across use cases, specific evaluations may be more relevant for certain use cases.

AA-Briefcase v1.1Updated

AA-Briefcase Elo

AA-Briefcase v1.1 is an agentic knowledge work benchmark developed by Artificial Analysis. AA-Briefcase Elo is a combined metric that aggregates rubric pass rate, analytical quality Elo and presentation Elo · Higher is better

AA-Briefcase Elo is a combined metric that aggregates analytical quality Elo, presentation Elo, and rubric pass rate, with rubric performance converted into Elo via synthetic head-to-head matches. Elo and 95% confidence interval bounds are clamped at 0.

AA-Omniscience

AA-Omniscience Index

AA-Omniscience Index (higher is better) measures knowledge reliability and hallucination. It rewards correct answers, penalizes hallucinations, and has no penalty for refusing to answer. Scores range from -100 to 100, where 0 means as many correct as incorrect answers, and negative scores mean more incorrect than correct.

Intelligence Index 比较

Intelligence Index vs. Cost per Intelligence Index Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task

Most attractive quadrant

Pareto line

Weighted average cost per Intelligence Index task. Each evaluation’s cost is calculated from input, cache hit, cache write, reasoning, and answer token prices, divided by task count, and weighted by its Intelligence Index weight.

Token 使用量

Output Tokens per Intelligence Index Task

Weighted average number of output tokens used to run one task in the Artificial Analysis Intelligence Index

The number of tokens required per Intelligence Index task. This is calculated by multiplying the output tokens per eval by the relative weights of each benchmark in the Intelligence Index, then dividing by task count (excluding repeats).

成本

Cost per Intelligence Index Task

Weighted average cost (USD) per Artificial Analysis Intelligence Index task, segmented by token type. Lower is better

Cost to Run Artificial Analysis Intelligence Index

Cost (USD) to run all evaluations in the Artificial Analysis Intelligence Index

The cost to run the evaluations in the Artificial Analysis Intelligence Index, calculated using the model's input, cache hit, cache write, reasoning, and answer token prices and the number of tokens used across evaluations (excluding repeats).

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens)

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

上下文窗口

Context Window

Context window: tokens limit · Higher is better

Larger context windows are relevant to RAG (Retrieval Augmented Generation) LLM workflows which typically involve reasoning and information retrieval of large amounts of data.

Maximum number of combined input & output tokens. Output tokens commonly have a significantly lower limit (varied by model).

常见问题

关于 Mistral Medium 3.1 的常见问题

Mistral Medium 3.1 发布于 2025年8月12日。

Mistral Medium 3.1 由 Mistral 开发。

Mistral Medium 3.1 在 Artificial Analysis Intelligence Index 上的得分为 9，在其他价格档位相近的非推理模型中高于平均水平（中位数：7）。

在 Intelligence Index 评测中，Mistral Medium 3.1 生成了 18M 个输出 token；与其他价格档位相近的非推理模型相比略高于平均水平（中位数：12M）。

否，Mistral Medium 3.1 不是推理模型。它不进行扩展的思维链推理，而是直接作答。

Mistral Medium 3.1 支持文本和图像输入。

Mistral Medium 3.1 支持文本输出。

是，Mistral Medium 3.1 支持图像输入，可以分析、描述图像并回答有关图像的问题。

是，Mistral Medium 3.1 是多模态模型，可以处理文本和图像输入并生成文本输出。

Mistral Medium 3.1 的上下文窗口为 130k 个 token。这决定了模型在单次请求中可以处理多少文本和对话历史。

否，Mistral Medium 3.1 是专有模型，其模型权重并未公开。

Mistral Medium 3.1 是专有模型，Mistral 尚未披露模型规模或参数量。

Mistral Medium 3.1 在 Artificial Analysis Intelligence Index 上的得分为 9。这项综合基准测试评估模型的推理、知识、数学和编程能力。

请查看服务商页面，了解当前 API 可用情况。查看服务商

请访问服务商页面查看可用情况。比较服务商

Mistral Medium 3.1 智能、性能与价格分析

模型摘要

智能Updated

速度

比较摘要

技术规格

此类别中有 299 个模型

速度

智能Updated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index

Open Weights

Intelligence Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

AA-Briefcase v1.1Updated

AA-Briefcase Elo

AA-Briefcase Elo

AA-Omniscience

AA-Omniscience Index

AA-Omniscience Index

Intelligence Index 比较

Intelligence Index vs. Cost per Intelligence Index Task

Cost per Intelligence Index Task

Artificial Analysis Intelligence Index

Token 使用量

Output Tokens per Intelligence Index Task

Output Tokens per Intelligence Index Task

成本

Cost per Intelligence Index Task

Cost per Intelligence Index Task

Cost to Run Artificial Analysis Intelligence Index

Cost to Run Artificial Analysis Intelligence Index

Pricing: Cache Hit, Input, and Output

Cache Hit

上下文窗口

Context Window

Context Window for RAG

Context Window

常见问题

Mistral Medium 3.1 何时发布？

谁开发了 Mistral Medium 3.1？

Mistral Medium 3.1 有多智能？

Mistral Medium 3.1 的回答有多冗长？

Mistral Medium 3.1 是推理模型吗？

Mistral Medium 3.1 支持哪些输入模态？

Mistral Medium 3.1 支持哪些输出模态？

Mistral Medium 3.1 能处理图像吗？

Mistral Medium 3.1 是多模态模型吗？

Mistral Medium 3.1 的上下文窗口有多大？

Mistral Medium 3.1 是开放权重模型吗？

Mistral Medium 3.1 有多少个参数？

Mistral Medium 3.1 在基准测试中的表现如何？

可以通过 API 使用 Mistral Medium 3.1 吗？

可以在哪里使用 Mistral Medium 3.1？