XM-Sparse improves sparse attention throughput using Netpreme X-Mem technology.
News Hub
What actually shipped in agent engineering, pulled from the labs, arXiv and Hacker News.
See who we followHiCache optimizes multi-parallelism and distributed serving for language models.
LMSYS published miniTE technical report on reinforcement learning with NVFP4.
LMSYS trained software engineering agents using Miles on MI355X GPUs for complex sandbox coordination.
SGLang AWS Trainium Plugin Beta announced.
SGLang-TorchTPU enables PyTorch-native production serving on TPU, built collaboratively by Google and Meta.
SGLang Low-Latency Mode optimizes kernels and runtime for faster inference.
NVFP4 KV cache accelerates long-context and agentic inference.
SGLang and Miles add day-zero support for DeepSeek-V4.1.
DeepSeek-V4-Flash and Kimi-K3 models can run on consumer hardware using SSD Expert Pack.
MiniMax-H3 achieves 1.95x lossless speedup on 8 H200 GPUs, scaling to 6.24x at reduced precision.
SGLang provides day-zero support for Qwen3.8-Flash-Next model.
Ling-3.0-flash uses speculative decoding on Blackwell to optimize batch-1 inference performance.
Mooncake converts fragmented rollout data into efficient bulk I/O operations.
LMSYS examined serving performance limits for DeepSeek-V4-Pro models.
LMSYS released Miles v0.1 for production-level post-training of language models.
Advanced CUDA Graph Techniques in Inference discusses optimization methods for model inference.
SGLang and Miles add day-0 support for Qwen3.8 model.
SGLang added immediate support for NVIDIA Nemotron 3.5 Lightning.
SGLang added immediate support for Muse Glimmer, a multimodal model designed for local agentic workflows.
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