GPU Cloud Engineering & Guides
Engineering deep dives, GPU optimization guides, and practical tutorials from the Jarvislabs team.
dstack x JarvisLabs: An Agentic Orchestrator for Your GPU Infrastructure
Run GPU training jobs on JarvisLabs through dstack. Learn the mental model, configure a fleet, and launch two hands-on runs.
Run Qwen3.6 MTP with llama.cpp on RTX PRO 6000
A hands-on tutorial for running Qwen3.6 MTP GGUF models with llama.cpp on a JarvisLabs RTX PRO 6000, including the exact commands and benchmark numbers from a single-GPU run.
OpenClaw x JarvisLabs: A Personal Assistant for Your GPU Cloud
Use OpenClaw with the JarvisLabs CLI to manage GPU instances, run experiments, monitor jobs, and send results back from chat.
How to Deploy NVIDIA NemoClaw on JarvisLabs
Deploy NVIDIA NemoClaw with local Nemotron 3 Nano 30B inference on a JarvisLabs GPU VM with enough VRAM. Kernel-level sandboxing for AI agents with no cloud API dependency.
How to Run PrismAudio on JarvisLabs
Run PrismAudio, the 518M parameter Video-to-Audio model from ICLR 2026, on a JarvisLabs A100 GPU. From setup to Gradio web UI in under 15 minutes.