Alibaba Cloud (Qwen)Qwen3.6-35B-A3BVSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend Qwen3.6-35B-A3B for practical local execution on standard developer hardware, or GLM-5.2 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While GLM-5.2 offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose Qwen3.6-35B-A3B for standard local setups, or GLM-5.2 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: GLM-5.2 is a massive 753B parameter model requiring heavy GPU infrastructure, while Qwen3.6-35B-A3B is a 35B parameter model.
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Benchmarks & Scores
Coding (swe-bench-pro)
49.5%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
86%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
Self HostLocal execution (zero API fees)Context Window
262.14k tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+12.6%)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+5.2%)
91.2%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.15Input: $1.40 | Output: $4.40Context WindowLarger
1.05M tokensFrequently Asked Questions about Qwen3.6-35B-A3B vs GLM-5.2
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 Qwen3.6-35B-A3B which scores 49.5%.
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