Real AI agent use cases, with sources and setup prompts

Run OpenClaw on a DGX Spark with a local Qwen model

He set up OpenClaw on an NVIDIA DGX Spark with a local Qwen3.6-35B-A3B served by vLLM in NVFP4, adding MTP-3 speculative decoding.

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Source

@vaishaksalin on X · 2026-10-18

Written in our own words. Credit to the original author. Link checked 2026-10-20.

What they did

He set up OpenClaw on an NVIDIA DGX Spark with a local Qwen3.6-35B-A3B served by vLLM in NVFP4, adding MTP-3 speculative decoding.

Result (as claimed)

About 93 tokens per second with a 262K context; he published the setup and numbers.

Tools they used

OpenClawQwenvLLM

Cost: OpenClaw: free plan, paid from Free. Checked 2026-10-14.

Set it up

  1. Pick a contained repo or task

    Start on a branch or side project where mistakes are cheap.

  2. Install and configure

    Set up OpenClaw, Qwen, vLLM. Read what it can run on your machine and limit permissions where possible.

  3. Run it on a real task

    Give it a well-scoped issue and let it work. Review the diff like any pull request.

  4. Add guardrails

    Keep tests and CI in the loop, and never let an agent push to main or touch production secrets unattended.

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Goal: Run OpenClaw on a DGX Spark with a local Qwen model
What the original author did: He set up OpenClaw on an NVIDIA DGX Spark with a local Qwen3.6-35B-A3B served by vLLM in NVFP4, adding MTP-3 speculative decoding.
Reported result (as claimed by the author): About 93 tokens per second with a 262K context; he published the setup and numbers.
Source: https://x.com/vaishaksalin/status/2111920716459503825
Tools they used: OpenClaw, Qwen, vLLM
Category: Dev & ops

Please:
1. Ask me 3 short questions about my situation (accounts I have, budget, what I want the output to look like).
2. Propose a step-by-step plan using these tools or cheaper alternatives, with the time and cost of each step. Use official pricing pages; say "check pricing" if unsure.
3. Then do the setup with me one step at a time, waiting for my OK before anything that sends messages, posts publicly, spends money or deletes data.
4. Finish with a checklist to run it again next time.

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Guides for this use case

How to self-host AI agents on a Raspberry Pi, Mac mini or homelab

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