NVIDIA GB300
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Headlines · 6
- Baseten cuts GPU-resident delta weight sync time to 15 seconds
Baseten redesigned its delta weight-sync path to use model weights already resident on GPUs as the parent copy, eliminating the need for a second full checkpoint in CPU memory. The company reports that syncing an approximately 770 GB GLM-5.3 checkpoint now takes 15 seconds with a 0.8-second request pause, versus 36 seconds and six seconds previously. Baseten also reports up to 3.2× higher output throughput per GPU at concurrency 48, while its Kimi K3 tests include an 8.4 GB delta applied across two GB300 nodes.
Baseten Blog · 🔥 5 - SGLang Reports Matching or Beating DeepInfer
DeepSeek open-sourced DeepInfer, the inference engine behind its own service, along with related kernels. In project-run tests using DeepInfer’s benchmarks and the same hardware, SGLang reached up to 1.04x prefill throughput on four GB300 or four B300 GPUs and cut decode step time by as much as 7.4% on 64 GB300 GPUs, according to the SGLang report. A 36氪 report said vLLM also approached or partly exceeded DeepInfer under its disclosed configurations. The comparisons used project-reported results and differing workloads and measurement methods.
LMSYS Blog · 🔥 0 - AWS stockpiles NVIDIA GB300 racks as power constraints bite
Business Insider, citing Amazon internal emails and documents, reported that AWS expected to receive about $5 billion in NVIDIA GB300 racks in August 2026 and roughly $3 billion more each month afterward. Some racks are being stored because data centers lack enough power, while an early-ownership process has pushed payments ahead of deployment. Amazon said staging completed hardware before power is ready is standard industry practice.
智东西 · 🔥 0 - Microsoft pulls out of Nscale's UK data center as grid power slips to the 2030s
Nscale said Microsoft has withdrawn from the Loughton, Essex data center the British neocloud firm was building for it, after UK grid authorities told Nscale not to expect a power supply until the 2030s; the site had been designed to host 23,040 Nvidia GB300 GPUs, starting at 50 MW and expandable to 90 MW. Microsoft was the only publicly announced customer, and Nscale says it remains committed to the project, is exploring alternative power sources and is looking at other UK expansion sites while calling its Microsoft relationship strong and long-term. The exit comes as Nscale seeks to raise as much as $3 billion in a US IPO, with Microsoft and Anthropic accounting for about 85% of its contracts, and Bloomberg reported investors pushing for a valuation of $16–19 billion against the roughly $30 billion Nscale had sought.
The Information · 🔥 0 - Blog SGLang Powers Beam in Production Reflection’s Beam is a 501B-parameter mixture-of-experts model with 23B active parameters per token, built for software engineering and long-horizon agentic tasks. SGLang Team October 16, 2026
On this page Highlights Model Architecture Hybrid Attention and Output Gating Dense Layers and Grouped MoE Routing SSMax Sandwich Normalization and Depth-Scaled Residuals Feature Support Dflash2 Speculative Decoding w/ Data-Parallel Attention Unified Memory for Target and Draft KV Heterogeneous TP for Prefill/Decode Disaggregation Reasoning, Tool Calls and LoRA BF16, NVFP4 and FP8 Model Support Prefix Reuse, Chunked Prefill and HiCache Optimizations Fusion Optimizations BF16 MoE Kernel Optimization TPU Support Reinforcement learning in Miles Validated Run Performance Result
LMSYS Blog · 🔥 0 - TokenSpeed reaches 685 output tokens/s per user on Qwen3.8-Flash-Next
Qwen's official X account congratulated LightSeek Foundation after its TokenSpeed inference engine reached 685 output tokens per second per user on Qwen3.8-Flash-Next. The run used 4× NVIDIA GB300 GPUs with NVFP4, and LightSeek published a blog post on the kernel and serving optimizations behind the result. Qwen said it is excited to see the community unlock more of Qwen's inference potential; the figure comes from LightSeek's own benchmark and has not been independently verified.
Qwen (X) · 🔥 0
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