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GPT-4o vs Mistral Medium 3.1

Compare GPT-4o and Mistral Medium 3.1 side-by-side. See how these vision models stack up in Open Prompt, Image Captioning, and OCR.

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OpenAIGPT-4o

GPT-4o is deprecated and can no longer be run. Details and evals are still available on its model page.

MistralMistral Medium 3.1
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OpenAI

GPT-4o vs Mistral Medium 3.1 Comparison Table

Evals updated August 20, 2026Pricing updated August 23, 2026

PropertyGPT-4oMistral Medium 3.1
OrganizationOpenAIMistral
Categoryclosedclosed
Modalitymultimodalmultimodal
Release DateMay 2024Aug 2025
Context Window128K128K
Parameters
LicenseProprietaryProprietary
Pricing per 1M tokens
Input $/1M$2.50$0.400
Output $/1M$10.00$2.00
Vision Tasks
CaptioningDemo
Chart Question Answering
Classification
Document Question Answering
Image Tagging
Multi-Label Classification
OCRDemo
Vision Language
Visual Question AnsweringDemo
Object Detection
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision

GPT-4o vs Mistral Medium 3.1: Overview

GPT-4o

GPT-4o (“omni”), released by OpenAI in May 2024, is a multimodal flagship model designed to unify text, image, and audio processing in a single system. Unlike earlier GPT-4 variants, GPT-4o supports real-time speech-to-speech interaction, enabling natural voice conversations alongside text and image reasoning. It features a context window of ~128,000 tokens for text input, with smaller output limits (commonly ~16K tokens), and has a knowledge cutoff of October 2023.

The model is optimized for efficiency and multilingual accessibility, supporting over 50 languages and covering ~97% of the world’s speakers. GPT-4o offers a cost-effective balance of speed and capability. It powers ChatGPT across free and paid tiers, making it widely accessible for applications in conversational AI, real-time translation, multimodal assistants, and global-scale communication tools.

Mistral Medium 3.1

Mistral Medium 3.1, released in August 2025 as the mistral-medium-2508 update, is a proprietary frontier model from Mistral AI positioned between smaller open models and high-end closed LLMs. It is multimodal, handling both text and image inputs, with a context window of ~128K tokens.

Compared to Mistral Medium 3.0, the 3.1 release introduces improvements in reasoning, coding, STEM, and enterprise workflows, along with better tone control for conversational and business applications. It is designed for scalable enterprise deployments, including hybrid cloud and on-premises VPC setups. As part of Mistral’s Premier line, Medium 3.1 is a commercial-only offering: while it delivers strong accuracy and performance, trade-offs include higher costs than open-weight models, restricted fine-tuning access, and increased latency/cost for very large contexts.