Model Profile: GPT-4o Mini (OpenAI)

Discover OpenAI's GPT-4o Mini, a smaller, cost-efficient multimodal model offering a balance of GPT-4 level capabilities with speed, ideal for high-volume tasks on allmates.ai.

Last updated 8 months ago

Tagline: Compact and cost-efficient multimodal intelligence.

📊 At a Glance

  • Primary Strength: Cost-Efficiency, Speed for its capabilities, Multimodality (Text, Vision).

  • Performance Profile:

    • 🧠 Intelligence: 🟡 Medium

    • ⏱️ Speed: 🟢 Faster

    • 💲 Cost: 🟢 Economy

  • Key Differentiator: Provides a smaller, faster, and cheaper version of GPT-4o's multimodal capabilities.

  • allmates.ai Recommendation: Best for Mates needing good general and vision capabilities at a lower cost and higher speed, suitable for high-volume or less complex tasks.

📖 Overview

GPT-4o Mini is OpenAI's smaller, cost-efficient version of the GPT-4 Omni model. Released in mid-2024, it's fine-tuned to maintain strong performance, particularly in vision and text understanding, at a fraction of the size and cost of its larger counterparts. GPT-4o Mini offers roughly GPT-4-level capabilities for many tasks but with significantly lower latency, making it an excellent choice for applications requiring quick responses and handling large volumes of interactions, such as customer-facing Mates or routine analysis tasks.

🛠️ Key Specifications

Feature Detail

Provider

OpenAI

Model Series/Family

GPT-4 (Omni series)

Context Window

128,000 tokens

Max Output Tokens

Typically 4,096 tokens (can vary)

Knowledge Cutoff

October 2023 (as per "LLM Model Profiles" document for GPT-4o Mini)

Architecture

Multimodal Transformer-based (Mini version)

Size Estimate

~8 Billion parameters (as per "LLM Model Profiles" document)

🔀 Modalities

  • Input Supported:

    • Text

    • Images

  • Output Generated:

    • Text

⭐ Core Capabilities Assessment

  • Reasoning & Problem Solving: ⭐⭐⭐✰✰ (Good)

    • Decent at reasoning through everyday problems and following instructions.

  • Writing & Content Creation: ⭐⭐⭐✰✰ (Good)

    • Produces coherent and contextually relevant content, suitable for emails, posts, and short articles.

  • Coding & Development: ⭐⭐✰✰✰ (Fair)

    • Can generate simple code and assist with routine scripts; less suited for complex coding.

  • Mathematical & Scientific Tasks: ⭐⭐✰✰✰ (Fair)

    • Handles basic arithmetic and can explain common scientific concepts.

  • Instruction Following: ⭐⭐✰✰✰ (Fair)

    • Follows instructions reasonably well for common tasks.

  • Factual Accuracy & Knowledge: ⭐⭐⭐✰✰ (Good)

    • Good general knowledge base; always verify critical information, especially post-cutoff.

🚀 Performance & 💰 Cost

  • Speed / Latency: Faster

    • One of its key selling points; designed for quick responses and high throughput.

  • Pricing Tier (on allmates.ai): Economy

    • Significantly cheaper than full GPT-4 class models (e.g., OpenAI priced it around $0.15/M input tokens).

✨ Key Features & Strengths

  • Cost-Efficiency & Speed: Drastically cheaper and faster than larger GPT-4 models.

  • Multimodal (Vision): Capably handles image inputs alongside text.

  • Balanced Performance: Offers a good trade-off between capability and resource usage.

  • High Volume Suitability: Ideal for applications with many interactions due to low cost and latency.

🎯 Ideal Use Cases on allmates.ai

  • High-Volume Chatbots: Customer support Mates handling many common queries.

  • Basic Image Analysis: Mates that need to understand or describe user-uploaded images (e.g., reading a form screenshot).

  • Routine Content Generation: Drafting simple emails, social media posts, or product descriptions in bulk.

  • Quick Summaries: Mates providing fast summaries of moderately sized texts or conversations.

  • Cost-Sensitive Applications: When GPT-4 level intelligence is desired but budget is a primary constraint.

⚠️ Limitations & Considerations

  • Complex Reasoning: May oversimplify or err on very complex logical or multi-step problems compared to full GPT-4o/GPT-4.1.

  • Nuanced Content: Might produce less rich or nuanced text than larger models.

  • Advanced Coding: Not recommended for highly intricate coding tasks or large codebase analysis.

  • Knowledge Depth: Smaller size might mean a slightly less detailed knowledge base.

🏷️ Available Versions & Snapshots (on allmates.ai)

  • gpt-4o-mini (Alias pointing to the latest recommended version)

  • gpt-4o-mini-[date-snapshot] (Specific snapshot if provided for consistency)