Alibaba Cloud (Qwen)Qwen3.6-PlusVSZ.ai (Zhipu AI)GLM-5
Our Take
We recommend Qwen3.6-Plus for superior overall value and reasoning capabilities, as it is cheaper or equal in cost while delivering peak intelligence. While Qwen3.6-Plus excels at complex complex codebases, multi-file repositories, and architectural planning, GLM-5 is suited for scripting multi-file code and clearly defined tasks. Choose Qwen3.6-Plus for architectural codebase planning, or GLM-5 if you specifically require its simpler functions profile.
▶WHY?
Benchmark Calculations & Evidence:
Coding Evaluation: Qwen3.6-Plus was evaluated on SWE-bench Pro (scoring 56.6%), while GLM-5 was evaluated on SWE-bench Verified (scoring 77.8%).
Reasoning Accuracy: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.6-Plus scored 90.4%, while GLM-5 scored 86%.
Cost Efficiency: GLM-5 pricing ($1/M input, $3.2/M output) is 0.7x cheaper than Qwen3.6-Plus ($0.5/M input, $3/M output).
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Benchmarks & Scores
Coding (swe-bench-pro)
56.6%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+4.4%)
90.4%graduate-level science QA
Cost & Context
Cost (per 1M tokens)1.4x cheaper
$1.13Input: $0.50 | Output: $3.00Context WindowLarger
1.05M tokensFrequently Asked Questions about Qwen3.6-Plus vs GLM-5
Qwen3.6-Plus is cheaper than GLM-5. Qwen3.6-Plus has a blended cost of $1.13/1M tokens, which is about 1.4x cheaper than GLM-5 at $1.55/1M tokens.
For coding tasks, Qwen3.6-Plus scores 56.6% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while GLM-5 scores 77.8% on swe-bench-verified (multi-file code and clearly defined tasks).
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