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name: vastai-sdk description: Vast.ai Python SDK — high-level API for GPU instances, volumes, serverless endpoints, and billing. allowed-tools: Python(vastai:*) compatibility: Python 3.9+ metadata: version: "1.0.1" author: vast-ai

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

bash
pip install vastai

For serverless and async support:

bash
pip install "vastai[serverless]"

Authentication

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

python
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:

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

VastAI Class (High-Level SDK)

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

Instance Management

python
# 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)
# ...as a jupyter instance on a direct connection
result = vast.create_instance(id=<offer_id>, image="pytorch/pytorch:latest", disk=50,
                              jupyter=True, direct=True, jupyter_lab=True)
# 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

python
# 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

python
# 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

python
# 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)

python
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

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

Team Management

python
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.

python
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 (SyncClient takes an InstanceConfig, not loose kwargs)
from vastai.data.instance import InstanceConfig
instance = client.create_instance(
    offer_id=<id>,
    config=InstanceConfig(image="pytorch/pytorch:latest", disk=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.

python
import asyncio
from vastai import AsyncClient
from vastai.data.instance import InstanceConfig
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>, config=InstanceConfig(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]"):

python
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

python
# 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)
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