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Hy3

hy.tencent.com

11–20 of 125 posts

Re: Hy3

#11
post #4

This model is shockingly small for how capable it is. its a little bit bigger than deepseekV4 flash but around as capable if not more on some benchmarks than V4 pro, i wouldnt be surprised if this becomes a popular local model.

> Hy3 has 295B parameters in total. To serve it on 8 GPUs, we recommend using H20-3e or other GPUs with larger memory capacity.

I would.

Re: Hy3

#12

Curious how people feel about this compared to DS4 Flash, given they are pretty close in size. Also curious how well it holds up to heavy quantization. DS4 Flash can currently run reasonably well on systems with ~96gb+ RAM, I wonder if Hy3 can compete there.

DS4-Flash is not only "significantly" smaller, it will also benefit from a lot more speed thanks to DSpark

Re: Hy3

#13
Been using this and GLM 5.2 back and forth. I like the speed of Hy3. Also seems very happy to follow instructions. Still haven’t found any open models that follow instructions as good as Mimo v2 pro though

Re: Hy3

#14
Quite interesting to see them and Meta and others release before OpenAI supposedly is to release GPT 5.6 today, would it be better to release it before or after? Calm before the storm type of thing?

Re: Hy3

#15

Curious how people feel about this compared to DS4 Flash, given they are pretty close in size. Also curious how well it holds up to heavy quantization. DS4 Flash can currently run reasonably well on systems with ~96gb+ RAM, I wonder if Hy3 can compete there.

Hy3 lacks the DSv4 architecture's KV Cache efficiency.

Whereas I can run DSv4 Flash on a pair of DGX Sparks and have enough memory left over for 3M tokens of KV cache, with Hy3 (quantized to FP4), there is only room for ~130K tokens of KV cache.

Re: Hy3

#16

Curious how people feel about this compared to DS4 Flash, given they are pretty close in size. Also curious how well it holds up to heavy quantization. DS4 Flash can currently run reasonably well on systems with ~96gb+ RAM, I wonder if Hy3 can compete there.

That's a 2-bit quant of DS4 flash. You're probably better off running Qwen3.6-27B at Q8.

Re: Hy3

#17

Curious how people feel about this compared to DS4 Flash, given they are pretty close in size. Also curious how well it holds up to heavy quantization. DS4 Flash can currently run reasonably well on systems with ~96gb+ RAM, I wonder if Hy3 can compete there.

DS4-Flash is not only "significantly" smaller, it will also benefit from a lot more speed thanks to DSpark

299B for Hy3 vs 284B* for Flash

Edit: fixed, got bad info

Re: Hy3

#18

Curious how people feel about this compared to DS4 Flash, given they are pretty close in size. Also curious how well it holds up to heavy quantization. DS4 Flash can currently run reasonably well on systems with ~96gb+ RAM, I wonder if Hy3 can compete there.

That's a 2-bit quant of DS4 flash. You're probably better off running Qwen3.6-27B at Q8.

I suspect it would depend on the task. DS4-flash does, as previously mentioned, handle quantization very well. Even at 2-bit it's still very coherent.

Re: Hy3

#19
post #3

I tried out the model it's pretty great, better than ~~gpt5.4~~ gpt-5.4-mini perhaps, atleast close enough to sonnet 5 in performance that I didn't notice much of a gap. Not really at gpt 5.5 tier though, and probably below glm 5.2... But most of all it just works for me for most things I tried and it's exceedingly cheap so there is no reason not to use it, if you need a foss model. Edited: gpt-5.4-mini not the base…

I think you’ve got the models wrong…gpt-5.4? I doubt there is any open source mode matching it. Maybe in a year

Re: Hy3

#20
post #3

I tried out the model it's pretty great, better than ~~gpt5.4~~ gpt-5.4-mini perhaps, atleast close enough to sonnet 5 in performance that I didn't notice much of a gap. Not really at gpt 5.5 tier though, and probably below glm 5.2... But most of all it just works for me for most things I tried and it's exceedingly cheap so there is no reason not to use it, if you need a foss model. Edited: gpt-5.4-mini not the base…

Hy3 DeepSWE - 28%

GPT5.4 xhigh DeepSWE - 52%

A lot of contaminated benchmarks in the blog post about Hy3, needs real testing though I have a distinct feeling it's benchmaxxed like a lot of Chinese models.

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