DeepSeekDeepSeek V4 FlashVSZ.ai (Zhipu AI)GLM-5.2
Our Take
We recommend DeepSeek V4 Flash 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 DeepSeek V4 Flash 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 DeepSeek V4 Flash is a 284B parameter model.
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Benchmarks & Scores
Coding (swe-bench-pro)
49.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)
80%graduate-level science QA
Cost & Context
Cost (per 1M tokens)12.3x cheaper
$0.17Input: $0.14 | Output: $0.28Context Window
1.05M tokensBenchmarks & Scores
Coding (swe-bench-pro)Winner (+13.0%)
62.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+11.2%)
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 DeepSeek V4 Flash vs GLM-5.2
DeepSeek V4 Flash is cheaper than GLM-5.2. DeepSeek V4 Flash has a blended cost of $0.17/1M tokens, which is about 12.3x 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 DeepSeek V4 Flash which scores 49.1%.
Related Matchups
Explore similar comparisons for DeepSeek V4 Flash and GLM-5.2.
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