DeepSeekDeepSeek V4 FlashVSZ.ai (Zhipu AI)GLM-5
Our Take
We recommend DeepSeek V4 Flash for practical local execution on standard developer hardware, or GLM-5 if you need peak reasoning and have the VRAM (or a cloud API) to host it. While GLM-5 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 for peak reasoning.
▶WHY?
Benchmark Calculations & Evidence:
Model Size: GLM-5 is a massive 754B parameter model requiring heavy GPU infrastructure, while DeepSeek V4 Flash is a 284B parameter model.
Was this recommendation helpful?
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)8.9x cheaper
$0.17Input: $0.14 | Output: $0.28Context WindowLarger
1.05M tokensBenchmarks & Scores
Coding (swe-bench-verified)
77.8%multi-file code and clearly defined tasks
Reasoning (gpqa-diamond)Winner (+6.0%)
86%graduate-level science QA
Cost & Context
Cost (per 1M tokens)
$1.55Input: $1.00 | Output: $3.20Context Window
202.75k tokensFrequently Asked Questions about DeepSeek V4 Flash vs GLM-5
DeepSeek V4 Flash is cheaper than GLM-5. DeepSeek V4 Flash has a blended cost of $0.17/1M tokens, which is about 8.9x cheaper than GLM-5 at $1.55/1M tokens.
For coding tasks, DeepSeek V4 Flash scores 49.1% 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).
Related Matchups
Explore similar comparisons for DeepSeek V4 Flash and GLM-5.
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.