๊ฐ€์ž… ํ›„ ์ดˆ๋Œ€ ๋งํฌ๋ฅผ ๊ณต์œ ํ•˜๋ฉด ๋™์˜์ƒ ์žฌ์ƒ ๋ฐ ์ดˆ๋Œ€ ๋ณด์ƒ์„ ๋ฐ›์„ ์ˆ˜ ์žˆ์Šต๋‹ˆ๋‹ค.

Marc Seal | Aevonix Research
@Kurcide
Founder, Aevonix | 36x DGX Spark Cluster | Building local SI agents with A.E.V.A. & Protagine | Sharing experiments, code & lessons from my Sparks & 6000 Pros
๊ฐ€์ž… April 2013
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GLM 5.3 Flash on 2x RTX PRO 6000 with TensorFold is out! ๐Ÿš€๐Ÿš€ Our one-command recipe for two RTX PRO 6000 GPUs. 2x RTX PRO 6000 (300 W per GPU): - 238 tok/s on prose, single stream - 449 tok/s on prose, 4 concurrent requests - 651 tok/s on structured output, 4 concurrent requests - Prefill up to 6,908 tok/s - Next turn in a 130K-token conversation: 0.51 s to first token - Up to 4 concurrent requests, 512K context What's new: - A recipe for 2x RTX PRO 6000: one host, half the GPUs of our 4x recipe - 512K context per request, two full 512K sessions at once (1.06M-token shared pool) - Vision on by default - One-time TP2 launch-table autotune - TensorFold v0.6.5 with the patch series from Mia's AI Lab and Aevonix Research, and the same exactness gates - One command: ./start.sh builds, downloads, compiles and serves Special thanks to @MiaAI_lab for the EXL3 quant, and to @ashxhart for TensorFold!
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