We provide a python CLI (open-source) for a convenient interface to the rest API. You can use the --explain option with any CLI command and it will print out the underlying API calls.
You can install the latest stable PyPI release with:
pip install vastaiAlternatively you can get the very latest version directly from github:
wget 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 functionality of the vast.ai website GUI and uses the same underlying REST API.
The CLI is self-contained in the single script file vast.py.
In order to authenticate most commands you will need to first login to the vast.ai website and get an 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 a 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-keys with anyone as they authenticate commands from your account.
Your default main key allows full access to all commands without limitations, but you can use the CLI to create additional keys with fine-grained access restrictions.
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:
vastai --helpTo see how the API works you can use it to find machines for rent.
vastai search offers --helpThere 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:
vastai 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:
vastai search offers 'reliability > 0.99 num_gpus>=4' -o 'num_gpus-'The output of this command at the time of this writing is
ID CUDA Num Model PCIE_BW vCPUs RAM Storage $/hr DLPerf DLP/$ Nvidia Driver Version Net_up Net_down R Max_Days machine_id
1596177 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
2459430 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
2459380 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
2456624 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
2456622 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
2456600 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
2455617 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
2454397 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
2405590 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
2364579 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
2281839 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
2281832 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
2452630 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
2342561 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
2237983 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
2459511 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
2448342 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
2437565 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
2332973 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
2459459 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
2459428 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
2459368 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
2458968 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
2458878 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
2458845 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
2458838 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
2454395 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
2452632 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
2450275 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
2449210 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
2445175 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
2444916 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
2437188 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
2437179 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
2431606 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
2419191 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
2405589 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
2392087 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
2377227 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
2349173 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
2338635 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
2303959 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
2281830 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
2193726 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
1737692 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 - 3510vastai create instance --helpYou create instances using the create instance command referencing an instance type ID returned from search offers. So to create an ssh direct instance of type 2459368 (using the ID returned from the search above for 4x 3090 on machine 4637) with the vastai/tensorflow image and 32 GB of disk storage:
vastai create instance 2459368 --image vastai/tensorflow --disk 32 --ssh --directOnce an instance is created, it then must first pull the image if it is not cached. After the image is loaded the instance boots and transititons to the running state.
You are charged for the resources you reserve. As storage is reserved at creation, storage charges begin when the instance is created and end only when it is destroyed.
GPU charges begin when the instance transitions to the running state, and end when it is stopped or destroyed.
vastai show instance --help
vastai show instances --helpvastai start instance --help
vastai stop instance --helpYou can stop an instance to avoid GPU charges, converting it into a storage unit - storage is usually very cheap compared to GPU. Starting an existing instance takes only a second or less whereas creating a new instance can take much longer (to pull a large docker image), so maintaining a pool of stopped instances is useful for many applications.
You can call stop/destroy instance from inside the instance using a special autogenerated instance apikey, to avoid exposing your main apikey.
vastai copy --help
vastai cloud copy --helpYou can copy data from a stopped instance to a running instance, to/from cloud storage, or to/from another machine.
vastai destroy instance --help
vastai destroy instances --helpOnce you are done with an instance make sure to destroy it to avoid ongoing storage charges.