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To find a Vast.ai GPU offer you can actually use, filter live offers against your job’s GPU model and VRAM needs, reliability, disk, network, access requirements, and total hourly price—not price alone. The CLI command vastai search offers is the starting point; after choosing an offer, register your SSH key, create an instance, wait for it to run, connect, and destroy it when finished.
Install the CLI and prepare access
Follow the current installation and authentication instructions in the official Vast.ai CLI guide. It documents both an install script and a PyPI installation route, plus configuring an API key. Installation details and flags can change, so use the guide’s current commands for your environment.
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Register your SSH public key before creating an instance. The CLI quick start places key registration ahead of instance creation; doing it first prepares the access path you will need to connect.
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Filter offers for your actual workload
Use vastai search offers and build a filter expression around what your job requires. The documented search fields include GPU name and count, GPU and CPU memory, disk, reliability, compute capability, network speeds, total hourly price, location, direct port count, verification status, and rentability. A filter narrows candidates; it cannot certify how a particular workload will perform.
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For example, adapt the official guide’s pattern for specifying a GPU name, count, verification, direct port, and rentability rather than copying it as a universal recipe. Add only the constraints your job needs. A single-GPU task, for instance, should not exclude multi-GPU offers unless that distinction matters to your setup.
- GPU and memory: Match the model, GPU count, and VRAM to the software and model you intend to run. Check CPU memory too if your workload needs substantial host RAM.
- Disk: Allow for the container image, dependencies, datasets, checkpoints, and outputs. A low-priced offer is not usable if its available disk cannot hold the job.
- Reliability: Set a minimum appropriate to how costly an interruption or failed run would be. The documentation exposes reliability as a filter but does not prescribe a universal threshold.
- Network and access: Consider network speeds, direct ports, and whether your workflow needs inbound access or file transfers. Requirements differ between a batch job and a service you need to reach.
- Location and price: Narrow by geography if latency, data location, or other regional constraints matter. Use a price cap based on the total hourly cost you can accept.
The default offer search uses verified on-demand offers and sorts by score. If you need to search without those default filters, use --no-default. You can also sort and limit results to make a shortlist manageable. The guide shows performance-per-dollar sorting, but a high score is not a substitute for checking workload fit, reliability, storage, network, access, and price.
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Compare the shortlist and check live prices
Compare candidates across the constraints that matter to your job, not just their listed GPU rate. Marketplace prices move continuously, so query current offers before deciding rather than relying on a saved quote or a static price example. The official pricing documentation describes the available pricing models and directs users to check live marketplace offers.
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Choose on-demand or interruptible pricing
The CLI documents on-demand, reserved, and bid (interruptible) searches. Use the mode that matches how much uncertainty your workload can absorb.
- On-demand: The documented instance-creation default is on-demand at
dph_totalunless you pass--bid_price. - Reserved: The CLI supports searching reserved offers; consult the current guide for the applicable syntax and terms before using this option.
- Bid / interruptible: A search with
--type bidexposesmin_bid, but finding such an offer does not by itself make creation bid-priced. Pass--bid_pricewhen creating the instance. An interruptible instance may be stopped when outbid, and storage charges can continue while it is stopped.
Bid pricing is a better fit for work that can resume after interruption than for a fragile, long-running job with no recovery plan. Checkpoint important work so it can restart from saved progress if the instance stops.
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Create, connect to, and stop an instance
- Choose an offer ID. From the filtered results, select an offer that meets your hardware, storage, network, reliability, location, access, and price requirements.
- Create the instance. Use the selected ID with the current CLI syntax. The official guide’s example is
vastai create instance <OFFER_ID> --image ... --disk ... --ssh --direct. Choose an image and disk allocation appropriate to your software and data. For bid pricing, include--bid_price; otherwise creation defaults to on-demand pricing atdph_total. - Check its status. Use the documented instance-status command and poll until the actual status is
running. Do not treat a returned SSH connection string as proof that the machine is ready. - Connect and transfer files. Retrieve the SSH URL using the CLI guide’s connection command, then use that connection string to connect from your terminal. The quick start also documents file transfer; use its current syntax for moving inputs and outputs.
- Destroy the instance when finished. Use the documented destroy command for the instance. The guide says destruction stops instance billing; do not leave an instance running unintentionally.
Common mistakes that lead to unusable offers or avoidable charges
- Choosing the cheapest result without checking fit: A low rate says nothing by itself about whether the GPU memory, disk, reliability, or network will work for your job.
- Misreading defaults: Search defaults are verified, on-demand offers;
--no-defaultremoves the default filters. Make sure the search scope matches what you intend to compare. - Assuming a bid search selects bid pricing:
--type bidaffects the search; creation needs--bid_priceto use bid pricing. - Ignoring interruption and storage costs: Outbid interruptible instances can stop, while storage charges may continue during the stopped period.
- Connecting too soon or leaving resources behind: Wait for
runningbefore connecting, and destroy the instance when the work is done.
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