GLM 5.3 Flash on two Sparks; Qwen3.8 Flash Next on one.
NVIDIA released a new FP4 quant of GLM 5.3 Flash made with quantization-aware distillation, which fits on 2x DGX Sparks or 2x RTX PRO 6000s and, per NVIDIA, keeps almost all of the BF16 quality, @MiaAI_lab reports. Single-Spark owners can now run Qwen3.8 Flash Next on TensorFold with the new quant: 256k context, five concurrent users, 46-55 tok/s single-stream and 132 tok/s across five streams, with a later update adding around 14% to prefill.
Too big for two Sparks, so a stranger lent four.
Ant Ling dropped weights for Ling 3.1 Flash: 560B total, 25B active, 1M context. On its own chart it beats GPT-5.6 Sol on 10 of 11 benchmarks and goes 5-5 with Opus 5, @sudoingX notes.
The door to local AI is already in most Steam rigs.
@sudoingX points out that the RTX 3060 is still the #1 desktop GPU on Steam and 16GB is now the most common VRAM, then lists what runs at each tier, including a 27B at 50.8 tok/s with 131k context on 12GB. He questions this week’s all-MoE releases, says the 20-30B dense class “has gone quiet,” and asks open labs for a 12B dense model.
Sandboxes, scaling and partner fine-tunes.
NVIDIA AI highlights Perplexity open-sourcing SPACE, the agent sandbox platform behind Computer, which gives developers more control over where agents run code and what they can access. It also posted a five-minute walkthrough of scaling a model endpoint on Kubernetes with NVIDIA Dynamo behind an OpenAI-compatible endpoint, plus a thread on partners post-training Nemotron 3.5 Super VL.