Qwen3.6

How To Run ZeroClaw in Docker with local LLMs (Qwen3 on an NVIDIA DGX Spark)

ZeroClaw is an open-source agent runtime. By default it expects a frontier model API key such as Claude, OpenAI, etc. This guide shows how to use a local Qwen3.6 model served by vLLM on an NVIDIA DGX Spark, routed through LiteLLM, with ZeroClaw and Firecrawl running in Docker on a separate host.

It also documents the onboarding bug I hit on a fresh install in v0.7.4 — ZeroClaw issue #6123 — and the config-only workaround.

vLLM Recipe: RedHatAI/Qwen3.6-35B-A3B-NVFP4 on DGX Spark

This is a vLLM Recipe - a production-ready Docker Compose configuration for running open-weight models on local hardware. It documents the exact setup, configuration rationale, and benchmark results so you can get a model running quickly. You are welcome to change the parameters to suit your workloads. This worked for me, so I hope you find it helpful.

This recipe covers Qwen3.6-35B-A3B-NVFP4 - a Mixture-of-Experts model with 35B total parameters but only ~3B active at inference - quantized to NVFP4 by Red Hat AI and running on the NVIDIA DGX Spark (my GigaByte AI Top Atom) with a GB10 Blackwell GPU and 128 GB of unified CPU/GPU memory.