DeepSeek V3.2 vs GLM 4.5V
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for DeepSeek V3.2 and GLM 4.5V.
DeepSeek V3.2
DeepSeek-V3.2 is a large language model designed to harmonize high computational efficiency with strong reasoning and agentic tool-use performance. It introduces DeepSeek Sparse Attention (DSA), a fine-grained sparse attention mechanism...
GLM 4.5V
GLM-4.5V is a vision-language foundation model for multimodal agent applications. Built on a Mixture-of-Experts (MoE) architecture with 106B parameters and 12B activated parameters, it achieves state-of-the-art results in video understanding,...
Technical Specifications
| Specification | DeepSeek V3.2 | GLM 4.5V |
|---|---|---|
| Provider | DeepSeek | Zhipu AI |
| Context Window | 131,072 tokens | 65,536 tokens |
| Agent Suitability | N/A | N/A |
| Time to First Token (TTFT) | N/A | N/A |
| Deployment Model | self hostable | managed api |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2025-12-01 | 2025-08-11 |
API Pricing Comparison
Input Price per Million Tokens
DeepSeek V3.2
$0.23
GLM 4.5V
$0.60
Output Price per Million Tokens
DeepSeek V3.2
$0.34
GLM 4.5V
$1.80
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
DeepSeek V3.2 Quirks & Gotchas
No developer gotchas reported.
GLM 4.5V Quirks & Gotchas
No developer gotchas reported.