AugmentClaude
MLDevOps

Vast.ai SDK

By vast-ai· vast-ai/vast-cli· 0

Manage GPU instances, volumes, and serverless endpoints on Vast.ai.

Installation

  1. Make sure Claude is on your device and in your terminal.

    Skills load from ~/.claude/skills/ when Claude Code starts up — so you need it on your machine first. If you don't have it yet, install it once with the command below, then run claude in any terminal to verify.

    One-time setup
    npm i -g @anthropic-ai/claude-code

    Already have it? Skip ahead.

  2. Paste into Claude Code or into your terminal.
    Install
    Sign up to copy
    Sign up free to reveal

    This copies the whole skill folder into ~/.claude/skills/vastai-sdk-vast-ai/ — the SKILL.md plus any scripts, reference docs, or templates the skill ships with. Safe default: works for every skill.

    Faster alternative (instruction-only skills)

    Skips the clone and grabs only the SKILL.md file. Don't use this if the skill ships Python scripts, reference markdowns, or asset templates — they won't be downloaded and the skill will fail when it tries to load them.

    Quick install (SKILL.md only)
    Sign up to copy
    Sign up free to reveal
  3. Restart Claude Code.

    Quit and reopen Claude Code (or any other agent that loads from ~/.claude/skills/). New skills are picked up on startup.

  4. Just ask Claude.

    Skills auto-activate when your request matches the skill's description — no slash command needed. Trigger phrases live in the skill's own frontmatter; you can read them in the “What this skill does” section above.

Prefer to read the source first? Open on GitHub.

When Claude uses it

Vast.ai Python SDK — high-level API for GPU instances, volumes, serverless endpoints, and billing.

What this skill does

Vast.ai Python SDK (vastai / vastai_sdk)

The vastai package provides a Python SDK for managing GPU instances, volumes, serverless endpoints, and billing on Vast.ai. The vastai_sdk package is a backward-compatibility shim that re-exports vastai.

Installation

pip install vastai

For serverless and async support:

pip install "vastai[serverless]"

Authentication

The SDK reads the API key from ~/.vast_api_key by default. You can also pass it explicitly:

from vastai import VastAI
vast = VastAI()                        # reads ~/.vast_api_key
vast = VastAI(api_key="YOUR_API_KEY")  # explicit key

Get your API key from https://console.vast.ai/manage-keys/

Backward Compatibility

The old vastai_sdk import still works:

from vastai_sdk import VastAI  # equivalent to: from vastai import VastAI

VastAI Class (High-Level SDK)

from vastai import VastAI
vast = VastAI(api_key=None, server_url=None, retry=3, raw=False, quiet=False)

Instance Management

# List all your instances
instances = vast.show_instances()

# Get a single instance
instance = vast.show_instance(id=12345)

# Search GPU offers
offers = vast.search_offers(query='gpu_name=RTX_4090 num_gpus>=4 reliability>0.99')

# Create an instance from an offer
result = vast.create_instance(id=<offer_id>, image="pytorch/pytorch:latest", disk=50)

# Lifecycle
vast.start_instance(id=12345)
vast.stop_instance(id=12345)
vast.reboot_instance(id=12345)
vast.destroy_instance(id=12345)

# Label an instance
vast.label_instance(id=12345, label="my-training-run")

# Get SSH connection string
ssh_url = vast.ssh_url(id=12345)   # returns "ssh -p PORT user@host"
scp_url = vast.scp_url(id=12345)   # returns scp-compatible URL

Interruptible (spot) rentals

Interruptible (spot) instances are priced below on-demand instances, but can be interrupted at any time by another user with a lower bid. Note: vast.search_offers(type='bid', ...) exposes min_bid, but vast.create_instance(...) defaults to on-demand at dph_total unless you pass bid_price=<floor>. Always pass bid_price after a type='bid' search, otherwise the instance will be rented as an on-demand instance/price instead of as an interruptible.

When outbid, the instance moves to stopped (not destroyed) and storage charges continue. Resume by raising the bid via vast.change_bid(id=..., price=...).

Search

# Search GPU offers (use help(vast.search_offers) for full query syntax)
offers = vast.search_offers(query='gpu_name=RTX_3090 num_gpus>=2')

# Search volume offers
volumes = vast.search_volumes(query='...')

# Search network volumes
net_vols = vast.search_network_volumes()

# Search templates
templates = vast.search_templates()

# Search invoices
invoices = vast.search_invoices()

Data Transfer

# copy() takes vast URLs: "[C.|V.]id:path", "cloud_service[.id]:path", or "local:path"
vast.copy("local:./data/", "C.12345:/workspace/data/")   # Local → instance
vast.copy("C.12345:/workspace/results/", "local:./out/") # Instance → local
vast.copy("12345:/workspace/", "67890:/workspace/")      # Instance → instance (legacy format)
vast.copy("s3.101:/data/", "C.12345:/workspace/")        # Cloud service → instance
vast.copy("V.1234:/file", "C.5678:/workspace/")          # Volume → instance
vast.copy("V.1234:/file", "s3.101:/workspace/")          # Volume → cloud service

vast.cancel_copy(dst_id=12345)                           # Cancel an in-progress copy

# Cloud sync via a saved cloud connection (see the UI settings page for connection IDs)
vast.cloud_copy(src="./data", dst="s3://bucket/path", instance=12345,
                connection=<conn_id>, transfer="Instance To Cloud")
vast.cancel_sync(dst_id=12345)

Volume copy is currently only supported for copying to other volumes, instances, or cloud services, not local. Do not use /root or / as a destination directory — it breaks ssh permissions on the instance and future copies fail. See https://vast.ai/docs/gpu-instances/data-movement#constraints.

Serverless Deployments

# List all deployments
deployments = vast.show_deployments()

# Get a deployment
deployment = vast.show_deployment(id=42)

# Delete a deployment
vast.delete_deployment(id=42)

Machine Management (Hosting)

machines = vast.show_machines()
machine = vast.show_machine(id=10)
vast.list_machine(id=10, price_gpu=0.30)
vast.unlist_machine(id=10)

SSH Keys

keys = vast.show_ssh_keys()
vast.create_ssh_key(ssh_key="ssh-rsa AAAA...")
vast.delete_ssh_key(id=5)

Team Management

members = vast.show_members()
vast.invite_member(email="user@example.com", role="developer")
vast.remove_member(id=7)

SyncClient (Low-Level Sync)

SyncClient provides typed, synchronous access to GPU offers and instances.

from vastai import SyncClient

client = SyncClient(api_key="YOUR_API_KEY")  # or reads ~/.vast_api_key

# Search offers with structured filters
offers = client.search(
    num_gpus=2,
    gpu_name="RTX_4090",
    min_reliability=0.99,
    max_dph_total=2.0,
)

# Create an instance
instance = client.create_instance(
    offer_id=<id>,
    image="pytorch/pytorch:latest",
    disk_gb=50,
)

# List your instances
instances = client.show_instances()  # returns list[SyncInstance]

# Destroy an instance
client.destroy_instance(instance_or_id=12345)

AsyncClient (Low-Level Async)

AsyncClient provides async access to GPU offers and instances. Use as an async context manager.

import asyncio
from vastai import AsyncClient

async def main():
    async with AsyncClient(api_key="YOUR_API_KEY") as client:
        # Search offers
        offers = await client.search(num_gpus=1, gpu_name="A100")

        # Create instance
        instance = await client.create_instance(offer_id=<id>, image="ubuntu:22.04")

        # List instances
        instances = await client.show_instances()  # returns list[AsyncInstance]

        # Destroy instance
        await client.destroy_instance(instance_or_id=instance.id)

asyncio.run(main())

Serverless Client

For inference endpoints (requires pip install "vastai[serverless]"):

import asyncio
from vastai import Serverless

async def main():
    serverless = Serverless()  # reads ~/.vast_api_key

    # Get an endpoint
    endpoint = await serverless.get_endpoint("my-endpoint")

    # Make a request
    response = await serverless.request("/v1/completions", {
        "model": "Qwen/Qwen3-8B",
        "prompt": "Who are you?",
        "max_tokens": 100,
        "temperature": 0.7,
    })

    text = response["response"]["choices"][0]["text"]
    print(text)

asyncio.run(main())

Common Patterns

# Find cheapest 4x RTX 4090 and launch a job
from vastai import VastAI
vast = VastAI()

offers = vast.search_offers(query='gpu_name=RTX_4090 num_gpus=4 reliability>0.99')
cheapest = min(offers, key=lambda o: o['dph_total'])
result = vast.create_instance(id=cheapest['id'], image="pytorch/pytorch:latest", disk=100)
print(f"Launched instance: {result['new_contract']}")

# Use help() to explore method signatures
help(vast.search_offers)
help(vast.create_instance)

Related skills

C

Claude API Helper

anthropics

Build, debug, and optimize Claude API applications with caching and model migration support.

OfficialComplete terms in LICENSE.txt
C

Customer Health Scorer

alirezarezvani

Analyze customer accounts to predict churn risk and identify expansion opportunities.

MIT
A

Adaptyv Protein Lab

foryourhealth111-pixel

Submit protein sequences for automated lab testing and validation experiments.

C

CLAUDE.md Optimizer

daymade

Optimize your CLAUDE.md file for clarity, efficiency, and maintainability.