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Mattias chaw
Mattias chaw

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VSCode + ZooCode + Chinese AI Models: Complete Setup Guide

#ai #aiwave #vscode #china

VSCode + ZooCode + Chinese AI Models: Complete Setup Guide

Published: 2026-07-07 | Category: Developer Tools | Reading Time: 8 min

If you're a developer looking to integrate Chinese AI models into your VSCode workflow, ZooCode is the bridge you need. It's a VSCode extension that turns any OpenAI-compatible API endpoint into a full-featured coding assistant — chat, inline completions, and code generation — right inside your editor.

This guide walks you through connecting ZooCode to AIWave, an OpenAI-compatible API gateway that provides access to 60+ Chinese AI models through a single endpoint. No multiple accounts, no separate SDK installations.

Why ZooCode?

You might wonder why not just use GitHub Copilot or Cursor's built-in AI. Fair question. ZooCode's advantage is model flexibility. Copilot locks you into OpenAI's models. Cursor uses Claude by default. ZooCode lets you pick any model from any vendor — and switch between them per-task.

This matters because:

  • No single model is best at everything
  • Model quality changes monthly — the leader today may not be the leader next quarter
  • Cost varies dramatically between models — DeepSeek V4 Flash is free to ultra-affordable, while premium models cost more
  • You might want Chinese models for Chinese codebases, Western models for English documentation

ZooCode decouples your editor from your model vendor. You get the best tool for each job.

Why Chinese AI Models for Coding?

Before diving into setup, let's address why you'd use Chinese models over the usual suspects:

  • Cost efficiency. DeepSeek V4 Flash costs $0.14/$0.28 per million tokens (input/output) — roughly 10× cheaper than GPT-4o while scoring 89.2% on HumanEval versus GPT-4o's 90.2%. The gap is negligible; the savings are not.
  • Massive context windows. DeepSeek V4 Flash supports 1M token context. DeepSeek V4 Pro also supports 1M. You can paste entire codebases into context.
  • Strong coding benchmarks. Qwen3 Coder (480B MoE) hits 88.4% on HumanEval. GLM-5.1 from Zhipu scores 87.0%.

The trade-off? Some models have slightly weaker English prose quality. For pure code generation, that's rarely an issue.

Prerequisites

  1. VSCode (latest stable)
  2. ZooCode extension — install from the VSCode Extensions Marketplace (search "ZooCode")
  3. AIWave account — sign up here (new accounts get $5 free credit)
  4. Your API key — found in the AIWave dashboard after login

Step 1: Get Your AIWave API Key

  1. Go to https://aiwave.live and log in (GitHub, Discord, Passkey, or Email)
  2. Navigate to the dashboard and copy your API key
  3. Note the Base URL: https://aiwave.live/v1

This Base URL is critical. ZooCode needs it to route requests through AIWave's OpenAI-compatible proxy.

Step 2: Configure ZooCode in VSCode

Open VSCode and launch ZooCode:

  1. Open Command Palette: Ctrl+Shift+P (Windows/Linux) or Cmd+Shift+P (macOS)
  2. Search: ZooCode: Open Settings
  3. The settings panel opens in a new VSCode tab

Enter the following values:

API Provider: OpenAI Compatible
Base URL: https://aiwave.live/v1
API Key: [paste your AIWave API key]
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Alternatively, if ZooCode supports JSON configuration, edit your settings file directly:

{
  "zoocode.provider": "openai-compatible",
  "zoocode.baseURL": "https://aiwave.live/v1",
  "zoocode.apiKey": "sk-your-aiwave-key-here",
  "zoocode.defaultModel": "deepseek-v4-flash",
  "zoocode.codeModel": "qwen3-coder-480b-a35b-instruct",
  "zoocode.maxTokens": 8192,
  "zoocode.temperature": 0.3,
  "zoocode.enableInlineCompletions": true,
  "zoocode.enableChat": true
}
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Step 3: Model Selection Strategy

Not all models are equal for all tasks. Here's the setup that works best:

Default Model: DeepSeek V4 Flash

  • Model ID: deepseek-v4-flash
  • Pricing: $0.14 input / $0.28 output per 1M tokens
  • Context: 1M tokens
  • HumanEval: 89.2%
  • Why it's the default: Best cost-to-performance ratio for general tasks. 1M context means you can throw entire project files at it. At these prices, you won't think twice about using it.

Code Model: Qwen3 Coder 480B

  • Model ID: qwen3-coder-480b-a35b-instruct
  • Pricing: $0.12 input / $0.36 output per 1M tokens
  • Context: 128K tokens
  • HumanEval: 88.4%
  • Why for coding: Alibaba's Qwen3 Coder is specifically trained for code. It's the most cost-effective dedicated coding model available. Even cheaper than DeepSeek V4 Flash on input tokens.

Free Fallback: GLM-4.7 Flash

  • Model ID: glm-4.7-flash
  • Pricing: FREE ($0.00/$0.00)
  • Context: 128K tokens
  • HumanEval: 72.5%
  • When to use: Quick questions, documentation lookups, non-critical tasks. It's completely free — use it liberally.

Step 4: ZooCode UI Walkthrough

Once configured, here's how to use ZooCode day-to-day:

Chat Panel

  1. Open ZooCode Chat: Click the ZooCode icon in the sidebar (or Ctrl+Shift+Z)
  2. Select model: Use the dropdown at the top of the chat panel. Your configured models appear here.
  3. Ask questions: Type naturally. "Explain this function," "Find the bug in this file," "Write unit tests for this module."

Inline Completions

ZooCode offers ghost-text suggestions as you type. To configure:

  1. Open Settings (Ctrl+,)
  2. Search "ZooCode"
  3. Toggle Enable Inline Completions on
  4. Set the code model to qwen3-coder-480b-a35b-instruct

The suggestions appear in greyed-out text. Press Tab to accept, Esc to dismiss.

File Context

ZooCode lets you attach files to your chat:

  1. In the chat panel, click the + button
  2. Select files from your workspace
  3. The file contents are included in the API request context
  4. With DeepSeek V4 Flash's 1M context window, you can attach dozens of files simultaneously

Step 5: Testing Your Setup

Create a test file to verify everything works:

# test_zoocode.py
def fibonacci(n):
    """Return the nth Fibonacci number."""
    if n <= 1:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)
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Open the ZooCode chat and ask:

"Optimize this fibonacci function for performance. The naive recursive approach is O(2^n)."

Expected response should include memoization or dynamic programming:

from functools import lru_cache

@lru_cache(maxsize=None)
def fibonacci(n):
    """Return the nth Fibonacci number. Memoized O(n)."""
    if n <= 1:
        return n
    return fibonacci(n - 1) + fibonacci(n - 2)
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Or an iterative version:

def fibonacci(n):
    """Return the nth Fibonacci number. Iterative O(n)."""
    if n <= 1:
        return n
    a, b = 0, 1
    for _ in range(2, n + 1):
        a, b = b, a + b
    return b
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If you get a coherent, correct response, your setup is working.

Cost Comparison: How Much Will You Actually Spend?

Let's estimate a typical workday:

Task Tokens (avg) Model Cost per task
Chat question 2K in / 1K out DeepSeek V4 Flash ~$0.0001
Code generation 5K in / 2K out Qwen3 Coder ~$0.0002
Code review 10K in / 3K out DeepSeek V4 Flash ~$0.0003
Documentation 8K in / 4K out DeepSeek V4 Flash ~$0.0003

Daily total (50 interactions): ~$0.015 — roughly $0.45/month for a full-time developer. Compare that to GitHub Copilot at $10/month or Claude Pro at $20/month.

Troubleshooting

"API key not recognized": Double-check you're using your AIWave key, not a key from another provider. The Base URL must be exactly https://aiwave.live/v1.

"Model not found": The model ID must match AIWave's catalog exactly. Use deepseek-v4-flash, not deepseek-v4-flash-2025-06-01 or other variant names.

Slow responses: Chinese models are served from Singapore. If you're in Europe or the Americas, expect 200-500ms added latency. For latency-sensitive work, consider using the free GLM-4.7 Flash ($0.00/1M) for quick tasks.

Next Steps

Chinese AI models have closed the quality gap while maintaining dramatic price advantages. There's never been a better time to integrate them into your daily workflow.

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