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CLI

Overview & Quickstart

8min

PyPI Install

You can install the latest stable PyPI release with:

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1pip install vastai


Github

Alternatively you can get the very latest version directly from github:

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1wget https://raw.githubusercontent.com/vast-ai/vast-python/master/vast.py -O vast; chmod +x vast;


This repository contains the open source python command line interface for vast.ai. This CLI has all of the main functionality of the vast.ai website GUI and uses the same underlying REST API. Most of the functionality is self-contained in the single script file vast.py, although the invoice generating commands require installing an additional second script called vast_pdf.py.

Quickstart

In order to authenticate most commands you will need to first login to the vast.ai website and get your api-key. Go to https://vast.ai/console/cli/. Copy the command under the heading "Login / Set API Key" and run it. The command will be something like:

vastai set api-key xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx

where the xxxx... is your unique api-key (a long hexadecimal number). Note that if the script is named "vast" in this command on the website and your installed script is named "vast.py" you will need to change the name of the script in the command you run. The set api-key command saves your api-key in a hidden file in your home directory. Do not share your api-key with anyone as it authenticates your other vast commands to your account.

Usage

For the most up to date help, use 'vast.py --help'. You can then get a list of the available commands. Each command also typically has help documentation:

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1vastai --help


To see how the API works you can use it to find machines for rent.

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1vastai search offers --help


There are many parameters that can be used to filter the results. The search command supports all of the filters and sort options that the website GUI uses. To find GPU instances with compute capability 8.0 or higher:

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1vastai search offers 'compute_cap >= 800 '


To find instances with a reliability score >= 0.99 and at least 4 gpus, ordering by num of gpus descending:

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1vastai search offers 'reliability > 0.99 num_gpus>=4' -o 'num_gpus-'


The output of this command at the time of this writing is

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1ID CUDA Num Model PCIE_BW vCPUs RAM Storage $/hr DLPerf DLP/$ Nvidia Driver Version Net_up Net_down R Max_Days machine_id 21596177 11.4 10x GTX_1080 5.5 48.0 257.9 4628 2.0000 73.0 36.5 470.63.01 653.3 854.5 99.5 - 638 32459430 11.5 8x RTX_A5000 9.1 128.0 515.8 3094 4.0000 209.4 52.3 495.46 1844.2 2669.6 99.7 12.0 4384 42459380 11.4 8x RTX_3070 6.3 12.0 64.0 710 1.4200 67.2 47.3 470.86 0.0 0.0 99.8 - 4102 52456624 11.4 8x RTX_2080_Ti 10.7 32.0 257.9 1653 2.8000 126.4 45.2 470.82.00 14.6 214.2 99.8 28.7 3047 62456622 11.4 8x RTX_2080_Ti 10.8 32.0 128.9 1651 2.8000 127.1 45.4 470.82.00 14.9 214.7 99.1 28.7 1569 72456600 11.5 8x RTX_2080_Ti 10.9 48.0 256.6 1704 2.4000 125.5 52.3 495.29.05 169.0 169.8 99.7 25.7 4058 82455617 11.2 8x RTX_3090 21.7 64.0 515.8 6165 6.4000 261.1 40.8 460.67 477.6 707.2 99.8 28.7 2980 92454397 11.2 8x A100_SXM4 22.4 128.0 2064.1 21568 13.2000 300.1 22.7 460.106.00 708.7 1119.8 99.2 - 4762 102405590 11.4 8x RTX_2080_Ti 11.2 48.0 257.9 1629 3.8000 125.5 33.0 470.82.00 389.4 608.8 100.0 1.8 2776 112364579 11.4 8x A100_PCIE 18.5 128.0 515.8 4813 14.8000 278.8 18.8 470.74 472.4 699.0 99.9 28.7 3459 122281839 11.2 8x Tesla_V100 11.8 72.0 483.1 1171 5.6000 193.6 34.6 460.67 493.0 697.8 100.0 28.7 2744 132281832 11.2 8x A100_PCIE 17.7 64.0 515.9 5821 14.8000 276.7 18.7 460.91.03 478.2 655.5 99.9 28.7 2901 142452630 11.4 7x RTX_3090 6.3 28.0 64.0 61 3.5000 165.5 47.3 470.86 84.6 84.4 99.3 3.8 4420 152342561 11.4 7x RTX_3090 6.1 96.0 257.6 1664 4.5500 149.2 32.8 470.82.00 476.9 671.7 99.4 1.7 4202 162237983 11.4 7x RTX_3090 12.5 32.0 257.6 3228 3.1500 204.5 64.9 470.86 194.4 183.8 99.1 - 4207 172459511 11.4 6x RTX_3090 6.2 - 128.8 812 2.8200 150.2 53.2 470.94 374.4 271.4 99.0 6.7 3129 182448342 11.5 6x RTX_A6000 12.4 64.0 515.7 6695 3.6000 169.8 47.2 495.29.05 668.6 1082.6 99.6 - 3624 192437565 11.4 6x RTX_3090 23.0 16.0 128.8 1676 5.4000 196.8 36.5 470.94 34.1 131.5 99.4 - 4238 202332973 11.2 6x RTX_3090 11.9 48.0 193.3 1671 3.3000 180.3 54.6 460.84 582.1 737.6 99.9 25.6 3552 212459459 11.5 4x RTX_3090 23.1 32.0 257.8 1363 2.0000 131.2 65.6 495.46 1954.7 2725.8 99.6 12.0 3059 222459428 11.5 4x RTX_A5000 24.6 64.0 515.8 1547 2.0000 104.9 52.4 495.46 1844.2 2669.6 99.7 12.0 4384 232459368 11.4 4x RTX_3090 25.3 48.0 64.2 133 1.3967 130.5 93.4 470.86 0.0 0.0 99.4 - 4637 242458968 11.6 4x RTX_3090 11.7 16.0 128.5 752 1.4000 79.8 57.0 510.39.01 797.8 842.7 99.9 4.0 2555 252458878 11.6 4x RTX_3090 11.6 36.0 128.5 1531 1.4000 81.9 58.5 510.39.01 757.1 807.6 99.9 4.0 3646 262458845 11.6 4x RTX_3090 3.1 12.0 128.5 369 1.4000 92.4 66.0 510.39.01 725.7 852.2 99.8 4.0 700 272458838 11.6 4x RTX_3090 5.7 48.0 128.9 624 1.4000 85.3 60.9 510.39.01 574.9 731.7 99.8 4.0 2217 282454395 11.2 4x A100_SXM4 22.9 64.0 2064.1 10784 6.6000 150.0 22.7 460.106.00 708.7 1119.8 99.2 - 4762 292452632 11.4 4x RTX_3090 6.3 16.0 64.0 35 2.0000 123.5 61.8 470.86 84.6 84.4 99.3 3.8 4420 302450275 11.4 4x RTX_3080_Ti 12.5 32.0 128.7 817 1.8000 128.8 71.6 470.82.00 278.3 350.4 99.7 - 4260 312449210 11.5 4x RTX_3090 11.2 48.0 128.9 324 2.0000 89.7 44.9 495.29.05 688.3 775.4 99.8 - 2764 322445175 11.4 4x RTX_3090 11.9 32.0 257.6 1530 2.0000 135.4 67.7 470.86 868.6 887.1 99.7 25.9 3055 332444916 11.4 4x RTX_3090 11.9 16.0 128.7 1576 1.4000 131.8 94.2 470.82.00 39.4 402.3 99.9 - 3759 342437188 11.4 4x Tesla_P100 11.7 24.0 95.2 2945 0.7200 44.8 62.2 470.82.00 10.9 76.2 99.5 0.1 3969 352437179 11.4 4x Tesla_P100 11.7 32.0 192.1 3070 0.7200 44.8 62.3 470.82.00 11.1 66.0 99.2 0.0 4159 362431606 11.4 4x RTX_3090 17.9 32.0 110.7 330 1.8400 134.3 73.0 470.82.01 584.6 813.4 99.7 4.4 4079 372419191 11.4 4x RTX_2080_Ti 6.3 32.0 64.4 837 2.0000 64.7 32.4 470.63.01 40.5 205.9 99.7 - 162 382405589 11.4 4x RTX_2080_Ti 10.8 24.0 257.9 815 1.9000 62.8 33.0 470.82.00 389.4 608.8 100.0 1.8 2776 392392087 11.4 4x RTX_A6000 10.8 32.0 515.9 1247 1.8000 64.5 35.8 470.94 669.9 705.4 99.1 10.9 4782 402377227 11.2 4x RTX_3090 6.3 24.0 64.3 1638 2.0000 128.3 64.1 460.32.03 37.8 145.0 99.7 3.0 2672 412349173 11.4 4x RTX_3090 23.2 48.0 128.7 1475 2.0000 107.4 53.7 470.86 33.2 84.2 99.8 47.3 3949 422338635 11.4 4x RTX_3090 23.0 32.0 128.5 3151 1.6000 108.8 68.0 470.86 33.8 86.4 99.6 47.4 3948 432303959 11.2 4x RTX_3090 11.7 28.0 128.8 791 2.1200 131.3 61.9 460.32.03 519.7 570.7 99.5 - 3042 442281830 11.2 4x A100_PCIE 18.1 32.0 515.9 2910 7.4000 143.6 19.4 460.91.03 478.2 655.5 99.9 28.7 2901 452193726 11.4 4x RTX_3090 12.4 32.0 128.8 1646 3.6000 153.9 42.8 470.82.01 33.3 137.5 99.5 - 3434 461737692 11.2 4x RTX_3070 6.3 28.0 128.5 656 2.8000 37.5 13.4 460.91.03 452.6 703.2 99.6 - 3510


Launching Instances

You create instances using the create instance command referencing a isntance type ID returned from search offers. So to create an instance of type 2459368 (using an ID from the search above for 4x 3090 machine 4637) with the vastai/tensorflow image and 32 GB of disk storage:

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1vastai create instance 2459368 --image vastai/tensorflow --disk 32




Updated 25 Mar 2024
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