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Qwen3.8-Max is the first in Qwen-Max series to be open-weight as well. Kimi K3, GLM 5.2 and now Qwen3.8-Max - open weight models. DeepSeek V4 Flash outperform

Qwen3.8-Max is the first in Qwen-Max series to be open-weight as well. Kimi K3, GLM 5.2 and now Qwen3.8-Max - open weight models. DeepSeek V4 Flash outperforming Gemini 3.1 pro, probably DeepSeek V4 Pro update is also coming soon Chinese labs are cooking very hard. US closed weight labs are probably hard time to resist not calling Washington DC for more AI regulations

badsectoracula 2mo ago
Kimi K3 is more like "weights available" in that you can download and use them but it is under a custom license that has a bunch of limitations where you have to pay Moonshot for doing some stuff. GLM 5.2 on the other hand is plain old MIT. Not sure how Qwen3.8-Max is going to be licensed, hopefully it'll be Apache like the smaller ones.
- pama 2mo ago
  You can do whatever you want with the model within your own organization. If you use it commercially—either as a model-as-a-service business or in a very large-scale product—you should check the additional license terms, which go beyond MIT. My interpretation is that Moonshot cares about the exact inference behavior and accurate representation of their model or derivatives, and perhaps also about capturing some additional value despite their own GPU limitations, so the extra license terms focus on those large-scale commercial deployments.
  - user43928 2mo ago
    Considering that very few orgs are going to be able to host a 3T parameter model internally, chances are most deployments would be subject to these restrictions and require a separate license from Moonshot.
    - pama 2mo ago
      Any US organization can rent compute.
    - andriy_koval 2mo ago
      probably will be few clicks in dashboard of your org's cloud provider.
      - deleted 2mo ago
        [deleted]
- Bnjoroge 2mo ago
  Kimi’s policy is extreme reasonable.
aleksandrm 2mo ago
US AI companies are already sweating and 100% pressuring the Trump administration for more anti-Chinese regulation, since there have already been talk of Trump considering banning Chinese models. There's however another push back from the startup industry urging them not to ban it, since it will stifle the innovation. In other recent news OpenAI also greatly cut their model prices, 20% for 5.6 Terra and 80% for 5.6 Luna, to stay competitive.
- qlte 2mo ago
  > In other recent news OpenAI also greatly cut their model prices, 20% for 5.6 Terra and 80% for 5.6 Luna, to stay competitive. I’ve seen comments on HN saying how bad this is for the Chinese model developers since the cheaper option like Deepseek Flash are not longer as price competitive to justify the hassle/risk/lack of multimodal… but isn’t this a gigantic red flag for OpenAI/Anthropic at their current valuations? Sure, it’s just the lowest end for now, and the enterprise money is at the top of the market. And there’s protectionism/enterprise lock-in/etc that complicate things somewhat. But still, if the US AI labs ever tap the training brakes for a millisecond, the “inference is still a money maker” argument seems to evaporate when they’ll immediately have to fight a race to the bottom until margins are virtually nothing. Or if the benchmaxing “line goes up” FOMO mindset starts to lose its luster and companies find their individual niches for productive use of AI and stop bothering with all the latest and greatest churn for top dollar. Which might be even worse if it means the training arms race is still ongoing but neither Anthropic or OpenAI want to be the first to “lose”. While the marginal value of each new model training run keeps decreasing and enterprises signal they’re more concerned with cost reductions than solving ARC-AGI-7 puzzles.
  - Bnjoroge 2mo ago
    Huh? V4Flash is still incredibly price competitive. The new version is right around GLM 5.2 and maybe slightly worse than opus 4.8 depending on which benchmark you use while being much cheaper(even factoring how most US zdr providers charge 10x Deepseek’s api caching price). K3 is also a tad behind fable/sol while being alot cheaper
wookmaster 2mo ago
I dont think they have a hard time resisting they did it a while ago, my company mandated everyone delete anything Chinese or Chinese derived back in April I think for no reason than "unsafe"

badsectoracula 2mo ago

Kimi K3 is more like "weights available" in that you can download and use them but it is under a custom license that has a bunch of limitations where you have to pay Moonshot for doing some stuff. GLM 5.2 on the other hand is plain old MIT. Not sure how Qwen3.8-Max is going to be licensed, hopefully it'll be Apache like the smaller ones.

pama 2mo ago
You can do whatever you want with the model within your own organization. If you use it commercially—either as a model-as-a-service business or in a very large-scale product—you should check the additional license terms, which go beyond MIT. My interpretation is that Moonshot cares about the exact inference behavior and accurate representation of their model or derivatives, and perhaps also about capturing some additional value despite their own GPU limitations, so the extra license terms focus on those large-scale commercial deployments.
- user43928 2mo ago
  Considering that very few orgs are going to be able to host a 3T parameter model internally, chances are most deployments would be subject to these restrictions and require a separate license from Moonshot.
  - pama 2mo ago
    Any US organization can rent compute.
  - andriy_koval 2mo ago
    probably will be few clicks in dashboard of your org's cloud provider.
    - deleted 2mo ago
      [deleted]
Bnjoroge 2mo ago
Kimi’s policy is extreme reasonable.

aleksandrm 2mo ago

US AI companies are already sweating and 100% pressuring the Trump administration for more anti-Chinese regulation, since there have already been talk of Trump considering banning Chinese models. There's however another push back from the startup industry urging them not to ban it, since it will stifle the innovation. In other recent news OpenAI also greatly cut their model prices, 20% for 5.6 Terra and 80% for 5.6 Luna, to stay competitive.

qlte 2mo ago
> In other recent news OpenAI also greatly cut their model prices, 20% for 5.6 Terra and 80% for 5.6 Luna, to stay competitive. I’ve seen comments on HN saying how bad this is for the Chinese model developers since the cheaper option like Deepseek Flash are not longer as price competitive to justify the hassle/risk/lack of multimodal… but isn’t this a gigantic red flag for OpenAI/Anthropic at their current valuations? Sure, it’s just the lowest end for now, and the enterprise money is at the top of the market. And there’s protectionism/enterprise lock-in/etc that complicate things somewhat. But still, if the US AI labs ever tap the training brakes for a millisecond, the “inference is still a money maker” argument seems to evaporate when they’ll immediately have to fight a race to the bottom until margins are virtually nothing. Or if the benchmaxing “line goes up” FOMO mindset starts to lose its luster and companies find their individual niches for productive use of AI and stop bothering with all the latest and greatest churn for top dollar. Which might be even worse if it means the training arms race is still ongoing but neither Anthropic or OpenAI want to be the first to “lose”. While the marginal value of each new model training run keeps decreasing and enterprises signal they’re more concerned with cost reductions than solving ARC-AGI-7 puzzles.
- Bnjoroge 2mo ago
  Huh? V4Flash is still incredibly price competitive. The new version is right around GLM 5.2 and maybe slightly worse than opus 4.8 depending on which benchmark you use while being much cheaper(even factoring how most US zdr providers charge 10x Deepseek’s api caching price). K3 is also a tad behind fable/sol while being alot cheaper

wookmaster 2mo ago

I dont think they have a hard time resisting they did it a while ago, my company mandated everyone delete anything Chinese or Chinese derived back in April I think for no reason than "unsafe"