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@lmsysorg
Large Model Systems Organization: We developed SGLang @sgl_project (https://sglang.io), Chatbot Arena (now @arena), and Vicuna!
AI
SGLang says it built the mode with NVIDIA and AMD; more low-latency kernels remain in progress.
AI
Reflection says the release includes Mirror CLI, its open-source training harness, and collaborations with 40-plus partners.
AI
finkd says the model runs well on new Mac Studios, crediting work with Apple and John Ternus.
AI
LMSYS reports 16-candidate scoring latency of 20.6 ms at the 95th percentile on Qwen3-8B with multi-item scoring, versus 54.1 ms using Generate.
AI
LMSYS says the cache uses about 56% of FP8's memory footprint per token and boosts long-context decoding throughput by up to 78%.
AI
LMSYS reports 3.33× end-to-end evaluation throughput with SGLang, which batches inference for 128 parallel environments on eight GPUs.
Technology
DeepSeek says its KV cache, which lets the model reuse earlier calculations, needs a quarter of the high-bandwidth memory and an eighth of the SSD storage required by the previous generation's cache.
AI
Mark Zuckerberg posted that Meta opened weights for a local model with another release planned soon.
