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. But ¥6 in / ¥18 out per M tokens — that's a real jump from Hy3's pricing.
First native multimodal in the GLM-5 family. MoE 320B / 18B active. Smartness 57 (~Opus 4.8). Native vision, 1M context. $0.15 in / $0.50 out per M tokens. A bit pricier than DeepSeek V4-Flash-Vision-Exp from a few days ago, but the smartness jump matters: V4-Flash-Vision-Exp only scores 40, and its vision is bolted on, not native.
. 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.
