Mistral Medium 3 offers state-of-the-art coding, reasoning, and multimodal capabilities at around one-eighth the cost of top competitors.
Introduction
Mistral Medium 3 is a commercial multimodal language model released in May 2025. It takes text and image as input, offers a whopping 128k-token window of context, and does amazingly well for professional applications like coding, data analysis, and document understanding. It runs best on just four GPUs in cloud or on-premises deployment, and is available via Mistral’s API or platforms including Amazon SageMaker, Azure AI Foundry, IBM watsonx.ai and NVIDIA NIM.
Enterprise‑Grade
Cost‑Efficient
Multimodal
On‑Premise Friendly
Review
Mistral Medium 3 offers state-of-the-art coding, reasoning, and multimodal capabilities at around one-eighth the cost of top competitors. Enterprise‑grade with hybrid and on‑premises support, it finds power, price, and flexibility in harmony. Critics describe it as offering “frontier‑class” accuracy at radically reduced cost, with quality performance similar to premium ones such as Claude Sonnet 3.7 and surpassing several open counterparts.
Features
Frontier‑Class Performance
Scores ≥ 90% of Claude Sonnet 3.7 on coding and STEM benchmarks, outperform models like Llama 4 Maverick and Cohere Command A.
Multimodal & Large Context
Text + images included, accommodates documents up to 128k tokens (~192 A4 pages).
Enterprise Deployment Flexibility
Deploy hybrid cloud or all on‑premises with at least four GPUs for secure, low‑latency deployment.
API & Ecosystem Integrations
Accessible via Mistral platform, Amazon SageMaker, Azure Foundry, IBM watsonx.ai, NVIDIA NIM, and Google Vertex AI.
Fine‑Tuning & Post‑Training
Enterprise consumers can post‑train or fine‑tune the model to fit internal data and workflows.
Best Suited for
Software Engineers
Rapid code generation, function calls, in-IDE debugging.
Data Analysts & Researchers
Ingestion of long documents and multimodal data for summarization and extraction.
Enterprise IT & Compliance Teams
Having sensitive data under control, on‑premise deployment enables regulatory compliance.
AI‑Driven Enterprises
Banking, healthcare, energy firms using bespoke AI agents and automations.
Strengths
Excellent performance‑to‑cost ratio – ~$0.40 input / $2 output per million tokens, offers ~90% premium model quality.
Excellent multimodal and long‑context processing.
Business agility with multiple deployment modalities and platform integrations.
Weakness
Proprietary weights aren’t open‑source, limiting transparency over the likes of Magistral Small.
Around slower than average in token processing rate (~77 tokens/sec), though latency is comparable (first token ~0.39 s).
Getting started with: step by step guide
Getting started with Mistral is easy:
Step 1: Choose Deployment Mode
Choose either hosted usage via Mistral API or self-hosted in cloud/on-premises with ≥4 GPUs.
Step 2: Access the Model
Register at Mistral AI and obtain API key. Or deploy on IBM watsonx, AWS SageMaker, Azure Foundry, Google Vertex, or NVIDIA NIM.
Step 3: Use Correct Model Endpoint
Call mistral-medium-2505 or call alias mistral-medium-latest using API for stability.
Step 4: Integrate Multimodal Inputs
Pass text and images in task requests like code generation, image captioning, or document Q&A.
Step 5: Optimize Usage
Control costs via pricing model ($0.40 input / $2 output per million tokens). Batching and context window adjustment are considerations.
Step 6: Customize & Fine‑Tune
Contact Mistral enterprise team to explore custom post-training or fine-tuning on in-house datasets.
Frequently Asked Questions
Q: Is Mistral Medium 3 free?
A: No, it is proprietary. Pay‑per‑use pricing: $0.40 input / $2 output per million tokens. Self‑hosting on ≥4 GPUs requires your own infra.
Q: Can I use it on-premises?
A: Yes, it supports a minimum of four GPUs and hybrid or VPC deployment for business use.
Q: Does it process images and long documents?
A: Yes, with multimodal input support and 128k token context.
Pricing
Mistral Medium 3 follows a token-based pricing model that ensures enterprise-grade AI performance at significantly reduced costs compared to leading competitors.
Token Type | Price per 1 Million Tokens |
Input Tokens | $0.40 |
Output Tokens | $2.00 |
Alternatives
Claude Sonnet 3.7
Better performance, much higher cost.
Magistral Medium
Mistral's chain-of-thought paywall proprietary reasoning model but for reasoning across multimodal
Llama 4 Maverick
Open-sourced, but lagging on benchmarks and multimodal performance.
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Mistral Medium 3
Mistral Medium 3 offers state-of-the-art coding, reasoning, and multimodal capabilities at around one-eighth the cost of top competitors.
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