GPT-5.2 vs GPT-4o mini

1. Advanced Reasoning for Diverse Domains

• Built to tackle coding and agentic workflows across multiple industries, with configurable reasoning support.

2. Multi-Modal & Long-Form Capabilities

• Handles both text and image inputs, producing text output:contentReference[oaicite:1]{index=1}.
• Allows up to 128 k output tokens for lengthy responses:contentReference[oaicite:2]{index=2}.

3. Large Context & Updated Knowledge

• 400 k token context window accommodates extensive codebases or documents:contentReference[oaicite:3]{index=3}.
• Knowledge cut-off of Aug 31 2025 keeps it current with recent developments:contentReference[oaicite:4]{index=4}.

1. Fast, cost-efficient performance

• Designed for low-latency, high-throughput workloads.
• Ideal for production systems where speed and budget matter more than deep reasoning power.

2. Great for focused NLP tasks

• Excels at classification, tagging, entity extraction, rewriting, paraphrasing, and SEO tasks.
• Strong at translation and keyword generation due to efficient language understanding.

3. Multimodal input capable (text + image)

• Accepts images for lightweight visual analysis, categorization, or extraction.
• Outputs text only, ensuring deterministic and easily integrated responses.

4. Supports advanced developer features

• Structured Outputs for predictable schemas.
• Function calling for building tool-augmented agents.
• Fully compatible with Batch API for large-scale processing.

5. Easy to fine-tune

• One of the best OpenAI models for domain-specific fine-tuning.
• Allows organizations to compress larger models' behavior (like GPT-4o) into a smaller footprint.

6. Suitable for distillation workflows

• Can approximate GPT-4o or GPT-5 outputs using distillation, dramatically reducing cost.
• Enables scalable deployment for high-volume applications.

7. Large context window for its size

• 128K context supports multi-step tasks, multi-document inputs, and long-running conversations.
• Useful for agents that need memory across extended sessions.

8. Reliable for commercial production

• Stable, predictable, and low-variance outputs make it ideal for automation and enterprise stacks.
• Works well in synchronous or asynchronous pipelines.