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OpenClaw Sets Practical Session on Building a Local AI Assistant With Ling-3.0-flash and DGX Spark

September 14, 2026 at 22:57 EDT

Foundation Models
AI Agents
Infra & Chips

OpenClaw is convening a practical session with Hugging Face, NVIDIA AI and AntLingAGI to show how to build a local AI assistant using Ling-3.0-flash on NVIDIA DGX Spark. The workflow demo and Q&A are scheduled for Sept. 17 at 10:30 a.m. SGT, or Sept. 16 at 7:30 p.m. PDT.

Sept. 17, 2026 · OpenClaw

A local AI assistant stack comes into focus

OpenClaw is hosting a hands-on workflow demo using Ling-3.0-flash and NVIDIA DGX Spark, with Hugging Face, NVIDIA AI and AntLingAGI participating.

124B

total parameters

5.1B

active per token

256K

context window

128GB

DGX Spark memory

Sparse model scale

124B

total capacity

5.1B

active per token

Each block represents roughly one active-parameter unit; Ling-3.0-flash keeps most of its 124B capacity inactive on each token.

Why developers care

The stack points toward private, local assistants for coding, research, document work and workflow automation.

What still matters

Setup depends on quantization, memory headroom, inference runtime choices and agent security controls.

Demo workflow

OpenClaw agent→Ling-3.0-flash→DGX Spark local inference→Workflow Q&A

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