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Alibaba Cloud (Qwen)Qwen3.6-PlusVSZ.ai (Zhipu AI)GLM-4.5

Analysis by:the whichllmmodel Editorial Team|Updated: June 2026

Our Take

We recommend Qwen3.6-Plus for complex complex codebases, multi-file repositories, and architectural planning, or the 1.1x cheaper GLM-4.5 if your budget requires optimizing costs for very high-volume pipelines. While Qwen3.6-Plus offers a clear reasoning advantage, it carries a moderate price premium. Choose Qwen3.6-Plus for architectural codebase planning, or GLM-4.5 to save on API costs for simple scripts.
WHY?
Benchmark Calculations & Evidence:
  • Coding Evaluation: Qwen3.6-Plus was evaluated on SWE-bench Pro (scoring 56.6%), while GLM-4.5 was evaluated on SWE-bench Verified (scoring 64.2%).
  • Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.6-Plus scored 90.4%, while GLM-4.5 scored 79.9%.
  • Cost Efficiency: GLM-4.5 pricing ($0.6/M input, $2.2/M output) is 1.1x cheaper than Qwen3.6-Plus ($0.5/M input, $3/M output).
  • Was this recommendation helpful?
    Model Specs

    Qwen3.6-Plus

    Benchmarks & Scores

    Coding (swe-bench-pro)
    56.6%

    complex codebases, multi-file repositories, and architectural planning

    Reasoning (gpqa-diamond)Winner (+10.5%)
    90.4%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)
    $1.13Input: $0.50 | Output: $3.00
    Context WindowLarger
    1.05M tokens
    Model Specs

    GLM-4.5

    Open SourceAPI Available

    Benchmarks & Scores

    Coding (swe-bench-verified)
    64.2%

    multi-file code and clearly defined tasks

    Reasoning (gpqa-diamond)
    79.9%

    graduate-level science QA

    Cost & Context

    Cost (per 1M tokens)1.1x cheaper
    $1.00Input: $0.60 | Output: $2.20
    Context Window
    131.07k tokens

    Frequently Asked Questions about Qwen3.6-Plus vs GLM-4.5

    GLM-4.5 is cheaper than Qwen3.6-Plus. GLM-4.5 has a blended cost of $1.00/1M tokens, which is about 1.1x cheaper than Qwen3.6-Plus at $1.13/1M tokens.

    For coding tasks, Qwen3.6-Plus scores 56.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while GLM-4.5 scores 64.2% on swe-bench-verified (multi-file code and clearly defined tasks).

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