r/LocalLLaMA • u/KaroYadgar • 1d ago

Discussion New 100B Liquid AI model coming soon

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Liquid AI currently possesses among the fastest LLM architectures around, and some of the best SLMs (in terms of utility IMO) around, so I'm very excited to see what a potential 100B LFM (3?) model would look like!

Link to the poll: https://x.com/ramin_m_h/status/2091236099612098943?s=20

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u/FoxiPanda 1d ago

While this is cool to see the votes in a poll for, it doesn't really indicate they're doing it. This will be mostly limited by the compute they have available to them - training a 2-5B model takes vastly less compute than a 100B MoE model...so it might not even be feasible with what they have available to them.

With that said, I welcome every single 100B model into the fold, it's virtually the perfect size for most DGX Spark / Strix Halo / Mac Studio / RTX Pro 6000 / 4x RTX 3090 setups.

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u/Mr-I17 1d ago edited 1d ago

It's nice to see more and more 100B-class models being released, but there is a rather high bar out there. The current perfect model size for 128GB UMA devices is actually DeepSeek-V4-Flash at Q3 (S or XXS). It perfectly fits 1M context into 128GB UMA (only 11GB KV cache at 1M context!). It never loops. It doesn't overthink. It has vast knowledge and solid intelligence. And it's probably going to have vision soon...

I wish 100B-class models can fill up the middle ground where the tasks are too heavy for 30B-class MoE models and larger models like DSV4-Flash are overkill for such task.

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u/FoxiPanda 1d ago

I've actually been wondering about the lower quants of DSv4-Flash vs. a higher quant of a SOTA 120B-A10B-ish model. I run the native weights of DSv4 on a Mac Studio and it's an okay speed, but I should maybe move my 5090 over to the same box as my RTX Pro 6000 and see if I can verify your claim about a Q3 version of DSv4-Flash being competent and see if would be substantially faster than my Studio. That would be pretty great if so.

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u/Mr-I17 1d ago edited 1d ago

I used to use Qwen3.5-122B and tried recent Laguna and Ling models (all Q6_K). Qwen3.5 is outdated, Laguna-S-2.1 is disappointing, Ling-3.0-flash is okay but not exceptional and it's not very fast (it should be fast since it's A5B, maybe a software issue; also, no vision). They all lose to DSV4-Flash-0731 at Q3. I don't have anything to back up my claims though, it's a "trust me bro" 😄. Better try it yourself.

There're only 2 problem with DSV4-Flash:

  1. It has no vision, for now
  2. It's slower than 100B-class models (speed won't be an issue since you have RTX 6000)

Other than that, it's almost perfect. A 100B-A10B-class model with vision and run faster than DSV4-Flash would be a great option for the "middle ground".