System requirements
Tabnine AI code assistant: System requirements
Tabnine client requirements
The Tabnine client runs as an IDE plugin/extension on the end user's machine.
Machine specs
OS/Arch of the following:
Windows (Windows 10+), x86_64 or i686
Linux (kernel 3.2+), x86_64
Mac OS (10.7+, Lion+), x86_64 or aarch64
8GB+ RAM
4+ CPU cores
Storage: 100 GB available space
Optional features additional requirements
Provenance and Attribution:
Storage: 1 TB available space
Supported IDEs
IDE | Minimal supported version | Latest supported version | Windows OS | Mac OS | Linux OS |
---|---|---|---|---|---|
VS Code | 1.68 | 1.95 | |||
JetBrains IDEs* | 2023.2 | 2024.3 | |||
Eclipse | 4.23 (2022-03) | 4.33 (2024-09) | |||
Visual Studio 2022 | 17.7.4 | 17.12 |
* JetBrains IDEs including IntelliJ, PyCharm, WebStorm, PhpStorm, GoLand, RubyMine, CLion, AppCode, Rider, DataGrip, and Android Studio
Network connection
Connection to the Tabnine cluster on port 443
Recommended for the initial install: Access to the IDE marketplaces (i.e., VS Code Marketplace, JetBrains Plugin Marketplace)
Permissions
Execute permissions for the following executables:
TabNine
TabNine-deep-local
TabNine-deep-cloud
WD-TabNine
TabNine-server-runner
vdb
jdtls
typescript-language-server
Write and execute permissions for the following machine paths:
Linux: ~/.config & ~/.tabnine
Mac OS: /Users/{{username}}/Library/Preferences & /Users/{{username}}/Library/Application Support
Windows: C:\Users\{{username}}\AppData\Roaming\
Tabnine cluster requirements (private installation)
Requirements for the Tabnine cluster in a private installation (Enterprise customers)
For code completions and Tabnine Chat in private installation
Tabnine can run on any modern Hyperscaler GPU. If you're interested in a GPU type not listed below, please contact our team to check compatibility.
Note: The following GPUs are not supported:
RTX6000
V100
T4
GPU nodes
Each node should have at least 512GB SSD.
Provider | Number of users | Minimal | Recommended | Unsupported |
---|---|---|---|---|
GCP | up to 100 | a2-highgpu-2g | a2-highgpu-2g | |
GCP | up to 1000 | a2-highgpu-2g | a2-highgpu-4g | |
AWS | up to 100 | g5.12xlarge | g5.12xlarge | |
AWS | up to 1000 | g5.12xlarge | g5.48xlarge | |
Azure | up to 100 | Standard_NC48ads_A100_v4 | Standard_NC48ads_A100_v4 | |
Azure | up to 1000 | Standard_NC48ads_A100_v4 | Standard_NC96ads_A100_v4 | |
On-premises server | Minimal | 2 * NVIDIA L40S GPU (see qualified system catalog) with at least 256GB RAM, 960 SSD and 32 CPU cores. With Nvidia driver >= 525.78.01 installed or 2 * A100 40GB | 2 * A100 80GB Nvidia qualified worker node (see qualified system catalog) with at least 256GB RAM, 960 SSD and 32 CPU cores. With Nvidia driver >= 525.78.01 installed or 2 * NVIDIA L40S (see qualified system catalog) with at least 256GB RAM, 960 SSD and 32 CPU cores. With Nvidia driver >= 525.78.01 installed | The following GPUs are not supported: * RTX6000 * V100 * T4 |
* Minimal: The minimum specifications required to run both code completions and chat. Recommended: Will provide better response times for code completions and chat.
** The cost may vary depending on the region and customer-specific agreements with the cloud vendor. Utilizing reserved instances instead of on-demand services can help lower pricing.
Domain Name System (DNS)
DNS configured with an A or CNAME record for the load balancer where the application will be exposed.
SSL certificate
SSL certificate and private key issued and signed by a Certificate Authority that you trust (key and certificate in pem format).
Network connection
Connection to Tabnine docker registry:
Host: registry.tabnine.com
IP: 34.72.243.185
Port: 443
Connection to Tabnine log gateway for collecting technical, aggregated metrics and logs (optional):
Host: logs-gateway.tabnine.com
IP: 34.123.33.186
Port: 443
DB
Redis minimal version: 6.2.11
PostgreSQL minimal version: 14.4
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