DeepSeekDeepSeek V4 ProVSZ.ai (Zhipu AI)GLM-4.7
Our Take
We recommend GLM-4.7 for practical local execution on standard developer hardware, or DeepSeek V4 Pro if you need peak reasoning and have the VRAM (or a cloud API) to host it. While DeepSeek V4 Pro offers frontier capability, its massive parameter size makes it extremely difficult to host locally. Choose GLM-4.7 for standard local setups, or DeepSeek V4 Pro for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: DeepSeek V4 Pro is a massive 1600B parameter model requiring heavy GPU infrastructure, while GLM-4.7 is a 358B parameter model.
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Benchmarks & Scores
Coding (swe-bench-pro)
52.1%complex codebases, multi-file repositories, and architectural planning
Reasoning (gpqa-diamond)Winner (+2.3%)
88%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$2.17Input: $1.74 | Output: $3.48Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (swe-bench-verified)
73.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)
85.7%graduate-level science QA
Cost & Context
Cost (per 1M tokens)2.2x cheaper
$1.00Input: $0.60 | Output: $2.20Context Window
202.75k tokensFrequently Asked Questions about DeepSeek V4 Pro vs GLM-4.7
GLM-4.7 is cheaper than DeepSeek V4 Pro. GLM-4.7 has a blended cost of $1.00/1M tokens, which is about 2.2x cheaper than DeepSeek V4 Pro at $2.17/1M tokens.
For coding tasks, DeepSeek V4 Pro scores 52.1% on swe-bench-pro (complex codebases, multi-file repositories, and architectural planning), while GLM-4.7 scores 73.8% on swe-bench-verified (multi-file code and clearly defined tasks).
Related Matchups
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