推論系統

推論 runtime、量化、 serving、KV cache、成本與效能。

GitHub Repo

Headlong Implements a Persistent Agent With an Infinite Bash Loop, Thinking and Acting Even When No One Is Asking

Laude Institute and MIT have open-sourced Headlong, a Bash-based system with fewer than 10,000 lines of code that treats messages as asynchronous observations within a continuous stream of thought rather than as new sessions. The design enables research into long-term memory and autonomous action, but it also turns token costs, permission isolation, and cross-user data boundaries into persistent risks.

最新模型

NVIDIA Adds Two-Stage Generation for MiniMax H3, Cutting 10-Second Video Latency to 14.9 Seconds on a Single GB200

H3 Super Acceleration first creates a low-resolution draft with four denoising steps, then uses LTX and Sol-Attn to complete high-resolution refinement in three steps. NVIDIA reports that 768p, 10-second video generation is 27.7× faster than the SGLang baseline, but the acceleration changes the sampling path and is not a pure kernel optimization at equivalent quality.

最新模型

ReWorld Uses a Pose-Indexed Landmark Bank to Fix the KV Budget, Allowing Interactive World Models to Return to Earlier Scenes After Long Journeys

ReWorld assigns short-term action control and long-term scene memory to different attention ranges, then preserves history in a fixed-capacity landmark bank. The authors demonstrate real-time streaming at 704×1280 and 64-second return trajectories, but only the paper and demo page are currently available; neither model weights nor code have been released.

GitHub Repo

DFlash 2 Drafts Tokens in Parallel for Qwen3.8-27B, but vLLM Nightly Currently Has Loading and VRAM Errors

DFlash 2 improves block-diffusion drafting with a candidate-path selector and dynamic convolution, delivering 2.7× to 3.4× the throughput of autoregressive decoding for Qwen3.8-27B in single-request tests. The latest reproducible issues show that vLLM nightly instantiates the wrong decoder layer and temporarily allocates nearly 4.74 GiB of extra memory before sharing vocabulary weights, potentially preventing startup on 24 GB GPUs.

硬體

MTIA 300 Integrates 12 RDMA NICs and Collective Communication Engines On-Chip, Avoiding PCIe and Compute-Core Contention

Meta has disclosed the system design of MTIA 300, which accelerates recommendation-model training with built-in NIC chiplets, near-memory reduction units, and compiled HCCL. The company says communication time across 40 accelerators was reduced to roughly one-quarter that of a reference GPU cluster, but provided no comparisons of cost, power consumption, or general-purpose LLM training.