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Life & fun · April 16, 2026

Flint – A 30B model fine-tuned for less repetition

As frontier LLMs have very little output diversity even for open ended queries. We built Flint to see if we could reverse this. It’s a finetuned Qwen3 30B model specifically trained to produce higher entropy when asked open ended questions. Flint significantly increases the NoveltyBench score compared to the base model, without significantly reducing the score on non-creative benchmarks like MMLU-STEM. This shows that that divergence tuning doesn't actually have to be a tax on base capabilities. Flint scores 7.47/10 on NoveltyBench while most frontier models score between 1.8 and 3.2.

Flint – A 30B model fine-tuned for less repetition launched on April 16, 2026 with 6 votes, #1,677 of 21,248 launches that month and more than 75% of that year's launches.

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What it does

While industrial AI races toward reasoning and accuracy, we realised that for creative industries, the 'correct' answer is often the least interesting one. So today, we’re introducing Flint . a model designed specifically to inspire, not give you the answers. We started Springboards with the mission to spark better ideas in people. But after building for three years, one thing has become impossible to ignore: frontier models are getting smarter, faster, and more polished, while their outputs are getting eerily similar and more repetitive. For a lawyer or an accountant, convergence can be a feature. For a strategist, writer, marketer, comedian or creative team, it is a bug. So we built the…from springboards.ai

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