Comprehensive side-by-side LLM comparison
GPT-5 Mini supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemini Diffusion is an experimental text and code generation model from Google DeepMind, announced at Google I/O in May 2025 as the first diffusion-based language model to achieve quality comparable to autoregressive models on standard benchmarks. Unlike transformer-based models that predict tokens sequentially left-to-right, it generates entire blocks of text by iteratively refining noise — the paradigm used in image and video generation models — enabling faster sampling speeds and stronger mid-generation error correction for code and mathematical editing tasks. At announcement it was available only as an experimental demo via waitlist, with no public API, marking it as a research milestone rather than a production deployment.
OpenAI
GPT-5 mini, released by OpenAI in August 2025, is a smaller variant from the GPT-5 family that inherits GPT-5's unified reasoning architecture and multimodal capabilities at a reduced inference cost. It targets high-volume production use cases requiring a balance of intelligence and response speed, offering GPT-5 capabilities for applications where full GPT-5 inference costs are a concern.
2 months newer

Gemini Diffusion
Google DeepMind
2025-05-20

GPT-5 Mini
OpenAI
2025-08
Context window and performance specifications
Available providers and their performance metrics
Gemini Diffusion
GPT-5 Mini
OpenAI
Gemini Diffusion
GPT-5 Mini
Gemini Diffusion
GPT-5 Mini