Open, Free & Better? Sonnet-Level Coding—And It’s FAST!

Quinn team introduces a new coding model based on their Quinn 3 series, considered one of their most significant models. It is the first open-weight model approaching the level of Cloude Sonnet 4.

The coding model by Quinn team excels beyond benchmarks and is solid based on early testing. It stands out for its unique qualities compared to other models like DeepSeek and Kimiku.

Quinn team offers a range of open-source and open-weight models, including embarratted models, reanker, and vision language models with exceptional performance.

Aside from the coding model, Quinn team also introduces Gemini CLI, enhancing the model's accessibility and usability for developers.

The model features 35 billion parameters, a window of 256 tokens, and excels in long horizon tasks such as agentic coding and browsing. It showcases top performance without compromising on reasoning and scaling.

With the potential to scale using 7.5 trillion tokens, the model boasts almost a trillion parameters and uses synthetic data for pre-training, marking a significant advancement in the field.

Quinn team's coding model competes with leading companies like Cloude Sonnet 4, delivering impressive performance in various environments and tasks with a focus on reasoning and accuracy.

The model's RKGI1 score signifies its importance, setting a benchmark for fairness and consistency across different model sets. The transparency and fairness of the model's evaluation are highlighted.

Exploring the user experience, the speaker shares personal examples of interactions and creations using the coding model, showcasing its potential in generating simulations, interactions, and mazes.