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Kimi K3.1 Pro has a 1-million-token context window and a Highspeed variant that runs 2-3 times faster. On Artificial Analysis's index it scores 55, fourth overall, while using 150M tokens against a median of 87M.
Moonshot also says it deliberately kept the open weights below its own pipeline's offensive-cyber capability.
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That simulated router sent the bulk of 1,030 real coding, legal and terminal tasks to Kimi K3, up to 96% in one category, cutting Fireworks' own bill by as much as 50x versus running Fable alone on the same work.
A regular Fireworks customer in the thread went further, accusing the company of inflating its own throughput numbers by 50-100% elsewhere, and pointing out that the router this whole post is built around isn't a product anyone can actually buy yet.
Z.ai's GLM-5.2 (744B total, 40B active) is now the top open-weights model on Artificial Analysis at 51, ahead of DeepSeek V4 Pro and Kimi K2.6, and it scored 1524 on one benchmark versus GPT-5.5's 1514.
The catch is verbosity: 43k tokens per task, 37k of it reasoning. One tester clocked 15 minutes and 45k tokens before the first file appeared. Sibylline's chief scientist still recommends it — pair GLM for writing with a cheap GPT sub for review, and you've got near-Opus output at a fraction of the price.
