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 Results for other workloads are historical and no longer updated.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 3.1. We suggest considering it instead.

Mistral

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Proprietary model

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Released May 2025

Mistral Medium 3 Intelligence, Performance & Price Analysis

Name: Intelligence
Creator: Artificial Analysis
License: https://artificialanalysis.ai/docs/legal/Terms-of-Use.pdf

Try it out API Provider Benchmarks

IntelligenceUpdated

Artificial Analysis Intelligence Index

* Estimated

Speed

N/A

Output tokens per second

Cost

In $0.40Out $2.00

N/A

Cost per Intelligence Index task

Verbosity

N/A

Output tokens from Intelligence Index

Mistral Medium 3 is above average in intelligence, but particularly expensive when comparing to other non-reasoning models of similar price. The model supports text and image input, outputs text, and has a 128k tokens context window.

Mistral Medium 3 scores 9 on the Artificial Analysis Intelligence Index, placing it above average among comparable models (median: 9).

Pricing for Mistral Medium 3 is $0.40 per 1M input tokens (expensive, median: $0.25) and $2.00 per 1M output tokens (expensive, median: $0.80).

Reasoning	No This page shows the non-reasoning version of this model. A reasoning variant may also exist.
Input modality	Supports: text and image
Output modality	Supports: text
Context window	128k ~192 A4 pages of size 12 Arial font

Metrics are compared against models of the same class:

Non-reasoning models → compared only with other non-reasoning models
Reasoning models → compared across both reasoning and non-reasoning
Open weights models → compared only with other open weights models of the same size class:

Tiny: ≤4B parameters
Small: 4B–40B parameters
Medium: 40B–150B parameters
Large: >150B parameters

Proprietary models → compared across proprietary and open weights models of the same price range, using a blended 3:1 input/output price ratio:

<$0.15 per 1M tokens
$0.15–$1 per 1M tokens
>$1 per 1M tokens

Highlights

Updated

Intelligence

Artificial Analysis Intelligence Index · Higher is better

Not publicly available

Speed

Output tokens per second · Higher is better

Cost per Task

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

Not publicly available

IntelligenceUpdated

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

Not publicly available

Estimate (independent evaluation forthcoming)

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

Not publicly available

Estimate (independent evaluation forthcoming)

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.

Benchmarks

Intelligence Evaluations

Intelligence evaluations measured independently by Artificial Analysis · Higher is better

Not publicly available

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

SciCodeUnder review

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

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-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.

Not publicly available

Intelligence Index Comparisons

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.

Cost

Cost per Intelligence Index Task

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

Not publicly available

Cost to Run Artificial Analysis Intelligence Index

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

Not publicly available

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)

Not publicly available

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.

Context Window

Context window: tokens limit · Higher is better

Not publicly available

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).

Frequently Asked Questions

Common questions about Mistral Medium 3

Mistral Medium 3 was released on May 7, 2025.

Mistral Medium 3 was created by Mistral.

Mistral Medium 3 scores 9 (estimated) on the Artificial Analysis Intelligence Index, placing it above average among other non-reasoning models in a similar price tier (median: 9).

Mistral Medium 3 costs $0.40 per 1M input tokens (at the higher end, median: $0.25) and $2.00 per 1M output tokens (at the higher end, median: $0.80), based on the median across providers serving the model.

Mistral Medium 3 costs $0.40 per 1M input tokens and $2.00 per 1M output tokens (based on the median across providers serving the model). For a blended rate (7:2:1 cache hit/input/output ratio), this is $0.56 per 1M tokens. Pricing may vary by provider. Compare provider pricing

No, Mistral Medium 3 is not a reasoning model. It provides direct responses without extended chain-of-thought reasoning.

Mistral Medium 3 supports text and image input.

Mistral Medium 3 supports text output.

Yes, Mistral Medium 3 supports image input and can analyze, describe, and answer questions about images.

Yes, Mistral Medium 3 is multimodal. It can process text and image input and generate text output.

Mistral Medium 3 has a context window of 130k tokens. This determines how much text and conversation history the model can process in a single request.

No, Mistral Medium 3 is proprietary. The model weights are not publicly available.

Mistral Medium 3 is a proprietary model and Mistral has not disclosed the model size or parameter count.

Mistral Medium 3 achieves a score of 9 on the Artificial Analysis Intelligence Index. This composite benchmark evaluates models across reasoning, knowledge, mathematics, and coding.

Yes, Mistral Medium 3 is available via API through 1 provider. Compare API providers

Mistral Medium 3 is available through 1 API provider. Compare providers

Mistral Medium 3 Intelligence, Performance & Price Analysis

Model summary

IntelligenceUpdated

Speed

Cost

Verbosity

Comparison Summary

Technical specifications

75 models in this class

Intelligence

Speed

Cost per Task

IntelligenceUpdated

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index by Open Weights / Proprietary

Artificial Analysis Intelligence Index

Open Weights

Benchmarks

Intelligence Evaluations

Intelligence Evaluation Relevance

Artificial Analysis Intelligence Index

AA-Omniscience

AA-Omniscience Index

AA-Omniscience Index

Intelligence Index Comparisons

Intelligence Index vs. Cost per Intelligence Index Task

Cost per Intelligence Index Task

Artificial Analysis Intelligence Index

Cost

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

Context Window

Context Window

Context Window for RAG

Context Window

Frequently Asked Questions

When was Mistral Medium 3 released?

Who created Mistral Medium 3?

How intelligent is Mistral Medium 3?

How much does Mistral Medium 3 cost?

What is Mistral Medium 3 API pricing?

Is Mistral Medium 3 a reasoning model?

What input modalities does Mistral Medium 3 support?

What output modalities does Mistral Medium 3 support?

Can Mistral Medium 3 process images?

Is Mistral Medium 3 multimodal?

What is the context window of Mistral Medium 3?

Is Mistral Medium 3 open source?

How many parameters does Mistral Medium 3 have?

How does Mistral Medium 3 perform on benchmarks?

Is Mistral Medium 3 available via API?

Where can I use Mistral Medium 3?