vast-gpu

vast-gpu is a skill for Claude Code from AI4Scientist/nano-scientist. It costs 46 tokens per session (4,119 once invoked), scanned A, original, no licence file.

A tool for renting, managing, and destroying GPU computers on Vast.ai, a marketplace for on-demand cloud GPU servers.

In plain words
What is it for?
Use it to rent cloud GPUs, manage their instances, and remove them when the work is finished.
Why use it?
It gives developers access to GPU hardware without buying or maintaining their own machine, while keeping control over the rented instances.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter.

Good fit Use it to rent cloud GPUs, manage their instances, and remove them when the work is finished.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ai4scientist/nano-scientist/vast-gpu
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add AI4Scientist/nano-scientist --skill vast-gpu
Clone the repo
git clone --depth 1 https://github.com/AI4Scientist/nano-scientist

Made for: Claude Code.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for vast-gpu

README.md
[![agentmods](https://agentmods.dev/badge/skills/ai4scientist/nano-scientist/vast-gpu/github.svg)](https://agentmods.dev/skills/ai4scientist/nano-scientist/vast-gpu)
Your own site
<a href="https://agentmods.dev/skills/ai4scientist/nano-scientist/vast-gpu"><img src="https://agentmods.dev/badge/skills/ai4scientist/nano-scientist/vast-gpu/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for vast-gpu

Your own site · 80×15
<a href="https://agentmods.dev/skills/ai4scientist/nano-scientist/vast-gpu"><img src="https://agentmods.dev/badge/skills/ai4scientist/nano-scientist/vast-gpu.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 46 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,119 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin unknown No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00046 $0.04119
Opus 5 $0.00023 $0.02060
Sonnet 5 $0.00009 $0.00824
Haiku 4.5 $0.00005 $0.00412

Measured 6d ago against content hash 2e8c182c9922, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

vast-gpu scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/skills-codex/vast-gpu/SKILL.md · 381 lines

The source is not reproduced here

No licence file

A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.

Read it on GitHub

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 381 lines · 46 tokens per session scan A 2e8c182c9922

Subscribe to this mod's changes

vast-gpu is a skill published in the GitHub repository AI4Scientist/nano-scientist (127 stars, last pushed 3mo ago), with no licence file. It adds 46 tokens to every session and 4,119 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

Related

Other skills, from other repositories

aris-serverless-modal

Run GPU workloads on Modal — training, fine-tuning, inference, batch processing. Zero-config serverless: no SSH, no Docker, auto scale-to-zero. Use when user says "modal run", "modal training", "modal inference", "deploy to modal", "need a GPU", "run on modal", "serverless GPU", or needs remote GPU compute.

OpenLAIR/dr-claw · 80 tokens

modal-serverless-gpu

Serverless GPU cloud platform for running ML workloads. Use when you need on-demand GPU access without infrastructure management, deploying ML models as APIs, or running batch jobs with automatic scaling.

OpenLAIR/dr-claw · 42 tokens

skypilot-multi-cloud-orchestration

Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.

OpenLAIR/dr-claw · 51 tokens

lambda-labs-gpu-cloud

Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.

OpenLAIR/dr-claw · 47 tokens

modal

Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs. Use when deploying or serving AI/ML models, running GPU-accelerated workloads (training, fine-tuning, inference), serving web endpoints, scheduling batch jobs, or scaling Python code to cloud containers with the Modal SDK.

K-Dense-AI/scientific-agent-skills · 65 tokens

ml-pipeline-workflow

Build end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.

foryourhealth111-pixel/Vibe-Skills · 48 tokens