Comprehensive side-by-side LLM comparison
GPT-5.2 leads with 27.2% higher average benchmark score. Overall, GPT-5.2 is the stronger choice for coding tasks.
OpenAI
GPT-4.1 nano is OpenAI's smallest member of the GPT-4.1 family, released in April 2025 alongside GPT-4.1 and GPT-4.1 mini as the latency-optimized, cost-minimized option for high-throughput applications. Positioned below GPT-4.1 mini in both size and cost, it was designed for use cases where speed and affordability dominate over raw capability — including tool calling, intent classification, short-form instruction following, and retrieval-augmented lookup tasks. Unlike its larger siblings, it supports fine-tuning, making it a practical candidate for task-specific customization at scale without incurring the cost of fine-tuning larger models.
OpenAI
GPT-5.2, released by OpenAI on December 11, 2025, is a large language model from the GPT-5 family that improves on GPT-5 in general intelligence, long-context understanding, agentic tool-calling, and vision. It features a 400K token context window, 128K maximum output tokens, and a knowledge cutoff of August 2025. GPT-5.2 targets long-context coding tasks, extended document analysis, and complex agentic workflows requiring reliable instruction following.
8 months newer

GPT-4.1 nano
OpenAI
2025-04-14

GPT-5.2
OpenAI
2025-12-11
Context window and performance specifications
Average performance across 1 common benchmarks
GPT-4.1 nano
GPT-5.2
Performance comparison across key benchmark categories
GPT-4.1 nano
GPT-5.2
GPT-4.1 nano
2024-06
GPT-5.2
2025-08
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
GPT-5.2
GPT-4.1 nano
GPT-5.2
GPT-4.1 nano
GPT-5.2