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wokey is a marketplace for LLM quota. It pairs people with unused plan credits to people who need more, and takes a 20% cut. Sellers keep 80% of what their credits earn; buyers save up to 90% of the official API price. I use it mostly for flagship models. The models check out as the real thing, cost less than going direct, and I skip the subscription jugglingling. If all you call are cheap models, a router still beats it. 🔗 https://wokey.ai/r/GKT1C78R
. 1.6T params, ~48B active, native multimodal, aimed at long-horizon agents, trained start to finish on Chinese hardware. Images get quantized into multi-level discrete tokens, and that's where Visual Coding and 3D pick up. On the RL side, failed trajectories get turned back into verifiable training tasks. W4A4 inference, 43% faster prefill. Meituan's own evals put it between Claude Opus 4.8 and Opus 5.
It stacks layers instead of parameters. The decoder has 32 layers, but layers 4 through 27 run twice with shared weights, so a forward pass does 56 layers of work while the checkpoint stays at 9B. Their own eval numbers: 71.38 on BIRD-Dev and 13.72 on AutomationBench, both above Qwen3.5-27B. Terminal Bench is still behind.
You've probably run into those short videos lately where an agent drives a phone around by itself. This one is called Mika, and it's a free open-source project. It's an Android app that works in the background through accessibility mode, so it can use pretty much any other app you have installed. Reply to someone on WeChat, scroll Xiaohongshu, drop something in a cart and check out. It finds the buttons by looking at the screen. There's no API to wire up, and it doesn't care what resolution your phone is. When it reaches a payment step or a captcha it stops and lets you finish. 🔗 github.com/wangzan101/Mika
