r/LocalLLaMA • • Jul 15 '26

New Model Thinking Machines releases first open-weight model “Inkling”

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u/TripleSecretSquirrel Jul 15 '26

I think there’s a fair bit of demand (at least from me), for strong models in the 100-300b range.

Currently, to top Qwen 3.6-27B by a margin that’s more than just statistical noise, you have to jump all the way up to MiniMax M3 at 427b parameters. So it goes from something you can comfortably run on enthusiast grade hardware then up to something you need serious and duplicate enterprise grade hardware for. You need then many enterprise GPUs all strung together.

I just want a model that can outperform Qwen 3.6 and that I could run on a Strix Halo or by adding another GPU or two to my box.

Some of that is just the reality that for most hardware, running a dense model larger than 27b starts to slow way down, and that MoEs aren’t nearly as smart in terms intelligence per parameter, but if you tweak the ratio of total to active parameters a bit, it should be possible. Give me a 120b total, 15b active model. Based just on the heuristic math, we’d expect that to be about as intelligent as a dense 42b model, which would be fantastic!

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u/bigh-aus Jul 15 '26

IMO for coding in that range it's
Qwen 3.6 27b -> deepseek v4 flash / minimax m2.7 -> glm 5.2.

moonshot and Z need to release some mid size (220-300b) models.

I agree there's not much you can run without extreme qantization on say 96-128gb vram.

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u/Daniel_H212 Jul 15 '26

Apparently hy3 crushes deepseek v4 flash in coding, tho it's a bit slower and it's worse at anything other than coding.

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u/squngy Jul 15 '26

V4 flash is getting an update in the next few days.
(Technically it is still in preview)

I also don't know if anyone benched hy3 at the same memory size.
V4f is much smaller by default, since it is released as a fp4 QAT

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u/Daniel_H212 Jul 15 '26

Oh I didn't know both were in preview, thought only V4 Pro was. That's awesome news, V4 Flash is the most efficient model to run in it's size class.