Ecosystem overviews

Most Western AI tooling treats Chinese models as an afterthought, a footnote in a catalogue otherwise organised around a handful of familiar labs. That framing has been out of date for a while. Several of the fastest-moving open-weights releases of the last two years came out of DeepSeek, Qwen, Moonshot, MiniMax and Zhipu, and ignoring them means paying more than necessary for capability you could have had.

Webparam lists both ecosystems with identical card layouts, identical depth of information and identical prominence. The Chinese section appears first, not as a quota, but because it is where the pace has been highest and where a discovery platform adds the most value.

• Open weights are far more common in the Chinese ecosystem, which matters for self-hosting and licence-constrained deployments
• Price-per-capability has generally been lower, particularly for coding and reasoning workloads
• Documentation and English-language support vary more between providers
• Data-residency and procurement rules may constrain provider choice regardless of technical fit

Apply the same method to both: define the task, eliminate on hard constraints, compare survivors, test on your own data. Provider pages carry each lab's history, strengths and research so the evaluation rests on substance rather than familiarity.