My quick thoughts on DSV4-Flash: Huge improvement over the original. It took 3 to 4 months, but we essentially got something close to GLM-5.2 in software engineering tasks.
I did some testing today on VS Code using cline plugin. DSv4-Flash is essentially free, so I’m going to keep it as a backup to GLM & Kimi’s latest models, since those coding plans are going to get used up quickly.
Going forward, I see 2 paths for open src/weight models:
Smaller models that can run locally with some souped up hardware.
Larger models that can need SuperNode to run and can compete with closed source flagship models.
All the developers are going to want to run these smaller LLMs locally. You don’t have to worry about AI company getting your data and can fine tune them anyway you want. This is going to drive an acceleration in “souped up” local hardware. Very bullish in my opinion for memory chips.
For the larger models, I think there really isn’t a lot of room for middle ground. You need to make them larger to compete fully with the Anthropic and OpenAI models.
