GLM 4.6vs
DeepSeek V3.2 Exp
GLM 4.6
vsCompare performance metrics, pricing, and capabilities of these AI models.
Key Differences
Context Length
Better
GLM 4.6: 203K (advantage)
DeepSeek V3.2 Exp: 164K (disadvantage)
Cost Efficiency
Higher Cost
Prompt: $0.50M vs $0.27M
Completion: $1.75M vs $0.40M
Capabilities
GLM 4.6
Modality: text->text
Inputs: text
DeepSeek V3.2 Exp
Modality: text->text
Inputs: text
Z
GLM 4.6
z-ai/glm-4.6
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K ...
Context Length203K
Prompt Price$0.50M
ReleasedSeptember 30, 2025
Supports:
text->textD
DeepSeek V3.2 Exp
deepseek/deepseek-v3.2-exp
DeepSeek-V3.2-Exp is an experimental large language model released by DeepSeek as an intermediate step between V3.1 and future architectures. It intro...
Context Length164K
Prompt Price$0.27M
ReleasedSeptember 29, 2025
Supports:
text->textDetailed Comparison
| Feature | GLM 4.6 | |
|---|---|---|
| Context Length | 203K | 164K |
| Prompt Price | $0.50M | $0.27M |
| Completion Price | $1.75M | $0.40M |
| Modality | text->text | text->text |
| Release Date | September 30, 2025 | September 29, 2025 |
Analysis & Recommendations
Quick Summary
This comparison reveals key trade-offs between GLM 4.6 and DeepSeek V3.2 Exp. GLM 4.6 offers a larger context window of 203K compared to DeepSeek V3.2 Exp's 164K, though GLM 4.6 comes at a higher cost.
GLM 4.6 Strengths
- •Larger context window (203K) for processing longer documents
- •Premium pricing for high-quality output
- •Specialized for text tasks
- •Latest generation model
DeepSeek V3.2 Exp Strengths
- •Competitive context size (164K)
- •More cost-effective per token
- •Specialized for text tasks
- •Proven and stable model
When to Use Each Model
Choose GLM 4.6 when:
- • You need the larger context window for complex tasks
- • Cost efficiency is not the primary concern in your use case
- • Working with text-based tasks that benefit from deep analysis
Choose DeepSeek V3.2 Exp when:
- • You need competitive context capability for long-form content
- • Cost efficiency is important for your budget
- • Working with text-based tasks that require advanced processing
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