I dunno, feels a bit unfair to companies that actually do FOSS releases (Gemma 4 being released under Apache 2.0 license) to compare them to a company that never done any FOSS releases, and mostly done proprietary "available to download" releases.
replyNote that a binary released under Apache 2.0 license does not yet make it FOSS.
replyAgreed, miles ahead though from "proprietary" which is what Meta been using for most model releases.
replyIdeally companies would share the fucking datasets and training code already, but no, no one wants to talk about the source of those or even share the ones they have as then who knows what comes out of Pandora's box...
NVIDIA does a pretty good job on that front.
replyIDK this model release is a bit disappointing considering the community has been chomping at the bit for the 124ba4b model. There was some leaked info about it but people suspect it was not released because it was too close to gemini flash in performance.
replyEvery other Google model I have tried felt very weak compared to qwen models. I dont have a ton of use case for multimodal though, so its very possible this is a fantastic multimodal model.
replyGemma 4 27b and 32b feel pretty capable for text and visionn. Comparable with qwen, maybe a bit better on tool calling heavy tasks
replyI am not overly impressed with the smaller gemma models. And gemma 3 was a bit of a mixed bag, great at some things, bad at most others
Hard disagree, Qwen multimodal is way better than google's, but Gemma 31b runs laps around Qwen 27B in complex engineering tasks. Maybe Qwen is better at slopcoding web framework CRUD, but for embedded dev there's no comparison.
replyqwen3.6 was my favorite, then I tried the deepseek-v4-{flash,pro}
replystill making my way through deep dives on the chinese open weights, they are all pretty good and way more cost / resource effective