AI HOT (Curated Pool)Jun 30, 2026, 05:06 UTC+8

Meituan's LongCat Owl Alpha tops OpenRouter, a 1.6T MoE trained entirely on Chinese ASICs

美团LongCat Owl Alpha：OpenRouter最流行模型，1.6万亿MoE，国产ASIC训练

Meituan LongCat's Owl Alpha became the most popular model on OpenRouter, consuming 10 trillion tokens so far. It's a 1.6T-parameter MoE trained on 35T tokens, running entirely on 50,000 Chinese ASICs. Performance is rated at Gemini/Opus 4.6 level, ranking #1 on Hermes Agent, #2 on Claude Code, and #3 on OpenClaw. The model will retire soon; no details on the next version yet.

Why it matters: Hits three high-signal zones at once: large-scale domestic ASIC training (50K chips), #1 on OpenRouter by usage (10T tokens burned), and claimed Gemini/Opus 4.6 parity. 1.6T MoE params and 35T training tokens are hard numbers, not marketing fluff. Only knock: the post doesn't ...

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Two numbers make this worth clicking: 1.6 trillion parameters, trained entirely on Chinese ASICs, and it's not a lab flex—it's the #1 model on OpenRouter by actual usage, with users burning through 10 trillion tokens. Owl Alpha ranks #1 on Hermes Agent, #2 on Claude Code, and #3 on OpenClaw, so people are genuinely using it for agent and coding tasks.

I'd discount the performance claim a bit. "Gemini or Opus 4.6 level" comes from the official tweet; the post doesn't share specific benchmarks or scores, so there's no way to verify. The ASIC details—chip model, interconnect, training stability—are also missing. And the model is retiring soon with no timeline for the next version, so jumping in now means a likely migration.

If those rankings hold up, the real signal is this: Chinese ASICs can now train a commercially viable giant MoE that people actually pay to call. That's harder evidence than any benchmark number.

Source: AI HOT (Curated Pool) · x.com
Published: Jun 30, 2026, 05:06 UTC+8 · Jun 30, 2026