[originalvichy]

Good news!

Friendly reminder: wait a couple weeks to judge the ”final” quality of these free models. Many of them suffer from hidden bugs when connected to an inference backend or bad configs that slow them down. The dev community usually takes a week or two to find the most glaring issues. Some of them may require patches to tools like llama.cpp, and some require users to avoid specific default options.

Gemma 4 had some issues that were ironed out within a week or two. This model is likely no different. Take initial impressions with a grain of salt.

[jjcm]

This is probably less likely with this model, as it’s almost certainly a further RL training continuation of 3.5 27b. The bugs with this architecture were worked out when that dropped.

[originalvichy]

Valuable note!

[Aurornis]

Good advice for all new LLM experimenters.

The bugs come from the downstream implementations and quantizations (which inherit bugs in the tools).

Expect to update your tools and redownload the quants multiple times over 2-4 weeks. There is a mad rush to be first to release quants and first to submit PRs to the popular tools, but the output is often not tested much before uploading.

If you experiment with these on launch week, you are the tester. :)