Comprehensive side-by-side LLM comparison
GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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.
Xiaomi
MiMo-V2-Flash, released by Xiaomi on December 16, 2025, is a Mixture-of-Experts large language model with 309 billion total parameters and 15 billion active parameters per inference, designed for high-speed reasoning and agentic workflows. It features a 256K token context window, processes up to 150 tokens per second, and was trained on 27 trillion tokens. MiMo-V2-Flash targets open-source deployments requiring fast, capable coding and reasoning with an efficient inference footprint, under an MIT license.
8 months newer

GPT-4.1 nano
OpenAI
2025-04-14
MiMo-V2-Flash
Xiaomi
2025-12-16
Context window and performance specifications
GPT-4.1 nano
2024-06
Available providers and their performance metrics
GPT-4.1 nano
OpenAI
MiMo-V2-Flash
GPT-4.1 nano
MiMo-V2-Flash
GPT-4.1 nano
MiMo-V2-Flash