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System Requirements

Tabnine AI code assistant: System requirements

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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 6.2+), x86_64

    • Mac OS (12+), x86_64 or aarch64

  • 16 GB+ RAM

  • 8+ CPU cores

  • Storage: 100 GB available space

Supported IDEs

IDE
Minimal supported version
Latest supported version
Windows OS
Mac OS
Linux OS

VS Code

1.85

1.108

JetBrains IDEs*

2023.3

2025.3

Eclipse

4.28 (2023-06)

4.38 (2025-12)

Visual Studio 2022

17.10

17.14

Visual Studio 2026 (beta β)

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* 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\

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Tabnine Deployment Options

Tabnine can be deployed in one of the following ways:

  1. Single/Multi-Tenant SaaS

  2. Private cloud / On-prem installation using private API endpoints

  3. Private cloud / On-prem installation using open-weight models

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Single/Multi-Tenant SaaS

This deployment allows you to utilize Tabnine’s private LLM endpoints to support both Chat and Agentic workflows.

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Models

These utilize the following families of LLMs for both Chat and Agent:

  • GPT

  • Claude

  • Gemini

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Hardware Requirements

None.

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Private Cloud / On-Prem Installation Using Private API Endpoints

You can install Tabnine on any of the leading private clouds (AWS, Azure, GCP) as well with an on-prem Kubernetes deployment while utilizing your own private endpoints to power Agentic workflows and the Chat model.

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Models

These utilize the following families of LLMs for both Chat and Agent:

  • GPT

  • Claude

  • Gemini

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Hardware Requirements

Tabnine requires a single GPU to support the software processes.; we recommend installing Tabnine on one H100 GPU.

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Private Cloud / On-Prem Installation Using Open-Weight Models

You can also power Tabnine by supporting open-weight models that are installed on-premises or on one of the private clouds mentioned above.

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Models

For Self-Hosted (SH) customers, your hardware needs depend on whether or not you already have any open-weight models within your infrastructure.

Tabnine-Supported Open-Weight Models

Devstral-Small-2-24B-Instruct-2512

Devstral-2-123B-Instruct-2512

MiniMax-M2.1

GPT-OSS-120B

GLM-4.7

Qwen-3-Coder-480B-A35B-Instruct

Qwen-3-30B (Chat only)

If not, we will install one of the following models on-premises for you:

Open-Weight Models that Tabnine Offers to Install On-Prem

Devstral-Small-2-24B-Instruct-2512

Devstral-2-123B-Instruct-2512

MiniMax-M2.1

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Hardware Requirements

There are different installation requirements, aimed to make sure users have the optimal experience when using Tabnine. Those requirements will be different for Agentic workflows or Chat.

Agent + Chat

Agent + Chat
≤100 Users — Recommended
≤100 Users — Minimal
101-500 Users — Recommended
101-500 Users — Minimal
501-1000 Users — Recommended
501-1000 Users — Minimal
1001-2000 Users — Recommended
1001-2000 Users — Minimal

Devstral-Small-2-24B-Instruct-2512

2 B200

2 H100

2 B200

3 H100

4 B200

6 H100

8 B200

12 H100

Devstral-2-123B-Instruct-2512

4 B200

4 H100

8 B200

8 H100

16 B200

8 B200

24 B200

16 B200

MiniMax-M2.1

2 B200

2 H200

4 B200

4 H200

8 B200

8 H200

16 B200

16 H200

GPT-OSS-120B

2 B200

2 H100

2 B200

2 H100

2 B200

4 H100

4 B200

8 H100

GLM-4.7

2 B200

8 H100

4 B200

2 B200

8 B200

4 B200

16 B200

8 B200

Qwen-3-Coder-480B-A35B-Instruct

2 B200

8 H100

4 B200

2 B200

8 B200

4 B200

16 B200

8 B200

Chat Only

Chat Only
≤100 Users — Recommended
≤100 Users — Minimal
101-500 Users — Recommended
101-500 Users — Minimal
501-1000 Users — Recommended
501-1000 Users — Minimal
1001-2000 Users — Recommended
1001-2000 Users — Minimal

Devstral-Small-2-24B-Instruct-2512

2 B200

2 H100

2 B200

2 H100

2 B200

2 H100

2 B200

4 H100

Devstral-2-123B-Instruct-2512

2 B200

4 H100

2 B200

4 H100

4 B200

8 H100

8 B200

16 H100

MiniMax-M2.1

2 B200

2 H 200

2 B200

2 H200 /

4 H100

2 B200

4 H200 /

8 H100

3 B200

8 H200

GPT-OSS-120B

2 B200

2 H100

2 B200

2 H100

2 B200

2 H100

2 B200

3 H100

GLM-4.7

2 B200

8 H100

2 B200

2 B200

4 B200

2 B200

6 B200

4 B200

Qwen-3-Coder-480B-A35B-Instruct

2 B200

8 H100

2 B200

8 H100

4 B200

4 B200

8 B200

8 B200

Qwen-3-30B

2 B200

2 H100

2 B200

2 H100

2 B200

2 H100

2 B200

2 H100

GPU Availability by Cloud Provider

GPU
AWS
Azure
GCP

H100

p5.4xlarge (H100 80GB)

NC40ads_H100_v5 (H100 94GB)

a3-highgpu-1g (H100 80GB)

H200

p5en.48xlarge (8×H200 141GB)

ND96isr_H200_v5 (8×H200 141GB)

a3-ultragpu-8g (8×H200 141GB)

B200

p6-b200.48xlarge (8×B200 HBM3e)

ND128isr_NDR_GB200_v6 (4×Blackwell 192GB)

a4-highgpu-8g (8×B200 HBM3e)

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If you don’t have an open-weight model that is not on the list, contact us and our team will work with you.

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Optional Features / Additional Requirements

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Provenance and Attribution:

Storage: 5 TB available space

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Domain Name System (DNS)

DNS configured with an A or CNAME record for the load balancer where the application will be exposed.

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TLS Certificate

TLS certificate and private key issued and signed by a certificate authority that you trust (key and certificate in PEM format).

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Network Connection

  • Connection to Tabnine container registry:

    • Host: registry.tabnine.com

    • IP: 34.72.243.185

    • Port: 443

  • Connection to Tabnine logs gateway for collecting metrics and logs (optional):

    • Host: logs-gateway.tabnine.com

    • IP: 34.123.33.186

    • Port: 443

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Databases

Databases

Redis version 6.5+

PostgreSQL version 15.0+

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Kubernetes

On-Premises Kubernetes ​Tabnine Enterprise can be installed on a new or existing Kubernetes cluster. For customers installing on a brand new Kubernetes cluster, we recommend the following minimum hardware specifications for the Kubernetes control-plane only (non-inclusive of Tabnine requirements).

Specs (Per Node)

HA

Non-HA

Number of Nodes

3

1

CPU

4 CPU

4 CPU

Memory

16 GB

16 GB

Disk

256 GB SSD

256 GB SSD

Network

1 GbE

1 GbE

Operating System

RHEL or Ubuntu

RHEL or Ubuntu

On-Premises

Specs (Minimum)

1 - 200 Users

201 - 500 Users

501-1000 Users

1001-2000 Users

2000+ Users

CPU

64

64

72

72

96

Memory

144 GB

144 GB

192 GB

192 GB

256 GB

Disk

10 TB SSD

10 TB SSD

16 TB SSD

16 TB SSD

32 TB SSD

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