Zed Editor

Use TensorX models as your AI coding assistant in Zed — the high-performance, open-source code editor.

Overview

Zed is an open-source code editor built for speed, with native AI integration via its Agent Panel. With 76K+ GitHub stars, it's one of the fastest-growing editors. Zed supports OpenAI-compatible providers, making it easy to connect to TensorX models.

Why Zed + TensorX?

⚡ Blazing fast — GPU-accelerated editor built in Rust
🤖 Built-in AI Agent — Inline assistant and Agent Panel
🔧 Tool use — AI can run terminal commands, edit files, search code
💰 Cost-effective — Use powerful open-source models instead of expensive proprietary ones
👥 Multiplayer — Real-time collaboration with AI assistance

Prerequisites

Zed (latest version) — download here
A TensorX API key (sign up here)

Setup

Step 1: Add TensorX as a Provider

Open Zed
Open the Agent Panel (Cmd+Shift+A on macOS / Ctrl+Shift+A on Linux)
Click Settings (gear icon) → Add Provider
Choose OpenAI Compatible and fill in:

Setting

Value

Provider Name

TensorX

API URL

https://api.tensorx.ai/v1

Step 2: Set Your API Key

Set the TENSORX_API_KEY environment variable. Zed derives the env var name from the provider name:

export TENSORX_API_KEY=your-tensorx-api-key-here

To make it permanent, add to your ~/.zshrc or ~/.bashrc:

echo 'export TENSORX_API_KEY=your-tensorx-api-key-here' >> ~/.zshrc

Step 3: Configure Models

Alternatively, configure everything via Zed's settings file (Cmd+, → Edit settings.json):

{
  "language_models": {
    "openai_compatible": {
      "TensorX": {
        "api_url": "https://api.tensorx.ai/v1",
        "available_models": [
          {
            "name": "z-ai/glm-5.1",
            "display_name": "GLM-5.1 ⭐",
            "max_tokens": 203000,
            "max_output_tokens": 16384,
            "capabilities": {
              "tools": true,
              "images": false
            }
          },
          {
            "name": "deepseek/deepseek-chat-v3.1",
            "display_name": "DeepSeek V3.1",
            "max_tokens": 164000,
            "max_output_tokens": 16384,
            "capabilities": {
              "tools": true,
              "images": false
            }
          },
          {
            "name": "deepseek/deepseek-r1-0528",
            "display_name": "DeepSeek R1",
            "max_tokens": 164000,
            "max_output_tokens": 16384,
            "capabilities": {
              "tools": true,
              "images": false
            }
          },
          {
            "name": "minimax/minimax-m2.5",
            "display_name": "MiniMax M2.5",
            "max_tokens": 197000,
            "capabilities": {
              "tools": true,
              "images": false
            }
          },
          {
            "name": "moonshotai/kimi-k2.5",
            "display_name": "Kimi K2.5",
            "max_tokens": 262000,
            "capabilities": {
              "tools": true,
              "images": true
            }
          }
        ]
      }
    }
  }
}

Step 4: Select Model

Open the Agent Panel and select a TensorX model from the model dropdown.

Recommended Models

Use Case

Model

Why

Coding ⭐

z-ai/glm-5.1

Top coding performance, strong reasoning

Reasoning

deepseek/deepseek-r1-0528

Complex analysis, architecture decisions

Functions

minimax/minimax-m2.5

Function calling, reasoning

Vision

moonshotai/kimi-k2.5

Image understanding, large context

General

deepseek/deepseek-chat-v3.1

Balanced performance and cost

Using the AI Features

Agent Panel

Open with Cmd+Shift+A (macOS) / Ctrl+Shift+A (Linux). The agent can:

Write and edit code across multiple files
Run terminal commands
Search your codebase
Explain code and answer questions

Inline Assistant

Select code and press Cmd+Enter (macOS) / Ctrl+Enter (Linux) to get inline AI suggestions.

Troubleshooting

Models Not Appearing

Ensure your TENSORX_API_KEY environment variable is set and Zed was restarted after setting it.

Authentication Errors

The API key env var name is derived from the provider name. If you named your provider "TensorX", the env var must be TENSORX_API_KEY.

Good afternoon