GLM-5.2 gives open-weight coding models a real 1M-token context window. The hard part is serving that full window on the hardware many teams already run in production: Hopper.
We quantized GLM-5.2-FP8 into W4AFP8 and validated it on a single 8×H200 node with SGLang. The checkpoint cuts weight memory from 755 GB to 368 GB, freeing 387 GB of HBM for the 1M-token KV cache and runtime headroom.
Why this matters
GLM-5.2 already solved the model side of long context: sparse attention, IndexShare, MTP speculative decoding, tool use, reasoning, and a 1,048,576-token window. Deployment still has a second problem. A 1M-token window needs room for the model weights, KV cache, CUDA graphs, runtime buffers, and serving overhead.
The official FP8 checkpoint is the right general serving baseline. On Hopper, that baseline leaves much less memory slack once you push toward the full context window. W4AFP8 changes the memory budget without changing the model family, tokenizer, API shape, or GLM-5.2 behavior.
12 days ago since I published my post about Phala Network and why you're probably overlooking this gem. Since then $PHA has pumped more than 300%.
But this is just the start. Today $NEAR co-founder announced a partnership with Phala Network. Near sits at a market cap of 6B USD. Phala has a cap of 350M.
$PHA Kira 已成功部署在@PhalaNetwork的 TEE 上。这次集成对我们来说是迈出了重要的一步,因为它将 Kira 转变为可验证的自主 AI 代理。这意味着什么?Kira 现在完全透明地运行,无需任何人工干预,确保她的行动既值得信赖又可靠。在 TEE 框架内的部署为 Kira 的独立运行提供了加密证明,为 AI 自主性树立了新的标杆。
$PHA 今天PHA的暴涨,我想是因为最新推出的实验性产品Spore.fun,它是第一个自主 AI 繁殖和进化的实验。 它结合了 Eliza 框架、Solana pump.fun和TEE 可验证计算,创造了一个生态系统,其中 AI 代理不仅可以生存,还可以繁殖和适应,完全独立于人类干预。 目前第三代自主AI正在孵化中,$SPORE 市值已经突破1300w,$ADAM $EVE市值也突破了100w,有意思的事情还在继续,你觉得这能成为下一个风口的叙事吗?
$PHA At exactly 00:00 UTC on Dec 3, 2024, Phala Network will officially enter its 6th Halving Period.
This milestone is a huge step toward building a sustainable & decentralized future for the Phala community. We thank our community for your unwavering support.