Qwen3 Coder Plus for OpenClaw: Pricing, Setup, and What It's Good At

Current as of March 2026. Qwen3 Coder Plus takes the context window to 998K — nearly a million tokens — with reasoning added. The output ceiling drops to 66K compared to base Qwen3 Coder’s 262K, but you’re getting a much larger input window in exchange. At $1/$5 per million, it’s priced between budget and frontier.

Specs

Provider	Qwen (Alibaba)
Input cost	$1.00 / M tokens
Output cost	$5.00 / M tokens
Context window	998K tokens
Max output	66K tokens
Parameters	N/A
Features	function_calling, reasoning

What it’s good at

998K Input Window

Drop in a full monorepo and let the model reason about it holistically. No RAG, no chunking, no missed cross-file references from retrieval misses.

66K Output

Enough for a substantial feature implementation or comprehensive documentation run. Not unlimited, but far beyond the 8K caps on many competitors.

Reasoning

The reasoning layer catches architectural issues and circular dependencies that straight code generation misses. More reliable for hard refactoring problems.

Where it falls short

Proprietary

Same licensing constraint as Qwen3 Coder. Not open-source.

Latency

Reasoning adds time. For large context inputs, you’ll wait noticeably before the first token appears.

Best use cases with OpenClaw

• Full-Repository Refactoring — The 998K window lets the model see the whole project at once. Changes in one module get validated against the rest without retrieval gaps.
• Technical Documentation — Feed in hundreds of source files and generate coherent docs. 66K output handles even large codebases.

Not ideal for

• Autocomplete or Fast Suggestions — Reasoning latency rules this out for anything real-time.
• Budget-tight Prototyping — At $5/M output, iterative agent loops with frequent regenerations add up quickly.

Run it through Haimaker

Skip juggling API keys. One Haimaker key gives you access to every model on the platform. Tell OpenClaw:

Add Haimaker as a custom provider to my OpenClaw config. Use these details:

- Provider name: haimaker
- Base URL: https://api.haimaker.ai/v1
- API key: [PASTE YOUR HAIMAKER API KEY HERE]
- API type: openai-completions

Add the auto-router model:
- haimaker/auto (reasoning: false, context: 128000, max tokens: 32000)

Create an alias "auto" for easy switching. Apply the config when done.

Or skip model selection entirely — Haimaker’s auto-router picks the best model for each task so you don’t have to.

OpenClaw setup

Point OpenClaw to api.haimaker.ai/v1 or your local Ollama instance. Ensure your timeout settings are high enough to accommodate the reasoning phase and large 66K output generation.

{
  "models": {
    "mode": "merge",
    "providers": {
      "qwen": {
        "baseUrl": "https://api.haimaker.ai/v1",
        "apiKey": "YOUR-QWEN-API-KEY",
        "api": "openai-completions",
        "models": [
          {
            "id": "qwen3-coder-plus",
            "name": "Qwen3 Coder Plus",
            "cost": {
              "input": 1,
              "output": 5
            },
            "contextWindow": 997952,
            "maxTokens": 65536
          }
        ]
      }
    }
  }
}

How it compares

• vs Qwen3 Coder — Base Qwen3 Coder gives 262K context with symmetric input/output limits. Plus gives 998K input but caps output at 66K. Choose based on whether you need bigger input or bigger output.
• vs GPT-4o — Qwen3 Coder Plus costs $1/M input vs GPT-4o’s $2.50/M, with a much larger context window. GPT-4o has better reasoning on hard problems.

Bottom line

If you’re tired of RAG retrieval misses and need to put nearly a million tokens of code in front of a model that can reason about it, this is the practical choice at this price point.

TRY QWEN3 CODER PLUS ON HAIMAKER

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For setup instructions, see our API key guide. For all available models, see the complete models guide.