Gemini Diffusion
by Google DeepMind
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About
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.
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Timeline
ReleasedMay 20, 2025
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License & Family
License
Proprietary
Performance Overview
Performance metrics and category breakdown
Overall Performance
1 benchmarks
Average Score
76.0%
Best Score
76.0%
High Performers (80%+)
0Top Categories
Coding
76.0%
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All Benchmark Results for Gemini Diffusion
Complete list of benchmark scores with detailed information
| MBPP | Coding | 76.00 | 76.0% | Unverified |