Alibaba Cloud (Qwen)Qwen3.6-PlusVSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend GLM-5.2 if your workflow requires peak coding capability, or the 1.9x cheaper Qwen3.6-Plus to optimize your API budget. While both models deliver similar reasoning performance, GLM-5.2 holds a clear lead in coding. Choose GLM-5.2 for complex development tasks, or Qwen3.6-Plus for cost optimization.
▶WHY?
Benchmark Calculations & Evidence:
Coding Benchmarks: Both models were evaluated on the SWE-bench Pro benchmark. Qwen3.6-Plus scored 56.6%, while GLM-5.2 scored 62.1%.
Reasoning Benchmarks: Both models were evaluated on the GPQA Diamond benchmark. Qwen3.6-Plus scored 90.4%, while GLM-5.2 scored 91.2%.
Cost Efficiency: Qwen3.6-Plus pricing ($0.5/M input, $3/M output) is 1.9x cheaper than GLM-5.2 ($1.4/M input, $4.4/M output).
Was this recommendation helpful?
Benchmarks & Scores
Coding (swe-bench-pro)
56.6%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
90.4%graduate-level science QA
Cost & Context
Cost (per 1M tokens)1.9x cheaper
$1.13Input: $0.50 | Output: $3.00Context Window
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+5.5%)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+0.8%)
91.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.15Input: $1.40 | Output: $4.40Context Window
1.05M tokensFrequently Asked Questions about Qwen3.6-Plus vs GLM-5.2
Qwen3.6-Plus is cheaper than GLM-5.2. Qwen3.6-Plus has a blended cost of $1.13/1M tokens, which is about 1.9x cheaper than GLM-5.2 at $2.15/1M tokens.
GLM-5.2 is better for coding tasks on this benchmark. It scores 62.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning) compared to Qwen3.6-Plus which scores 56.6%.
Related Matchups
Explore similar comparisons for Qwen3.6-Plus and GLM-5.2.
Do you want to find a model for your constraints?
Use our interactive model finder to filter LLMs by reasoning capability, coding performance, cost, and context length.