GPT-5.6 Luna just dropped 80% in price.
Ran the numbers against DeepSeek-v4-Pro. Luna wins for what I need, so I'm moving my subagent slot over to it.
Setup right now: Grok-4.5 or Kimi-K3 orchestrating, Luna doing the actual work.
GPT-5.6 Luna just dropped 80% in price.
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DeepSeek-V4-Flash just dropped. It's eating GLM-5.2 alive.
Same params, no new architecture — just post-training. Per the official writeup, it now tops multiple agent benchmarks. DeepSWE: 7.3 → 54.4 Terminal Bench 2.1: 82.7, nipping at Opus-4.8's 85 If the Flash tier is already this strong, V4-Pro at release is going to be unhinged.
trying to build a paid product
. just needed a multimodal model that's actually good AND doesn't bleed me dry. tried everything on the shelf, only Xiaomi's MiMo-V2.5 fit lol every popular LLM rn is basically a one-trick pony — killer at one thing, mediocre at the rest. you really can't have it all.
Meituan shipped LongCat-2.5
. 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.
SenseTime open-sourced SenseNova Loop-9B-Preview.
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.
