Model Comparison

DeepSeek VL2 Tiny vs GLM-4.5

Comparing DeepSeek VL2 Tiny and GLM-4.5 across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 Tiny and GLM-4.5 don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Mon Apr 20 2026 • llm-stats.com
DeepSeek
DeepSeek VL2 Tiny
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Zhipu AI
GLM-4.5
Input tokens$0.40
Output tokens$1.60
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

352.0B diff

GLM-4.5 has 352.0B more parameters than DeepSeek VL2 Tiny, making it 11733.3% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Zhipu AI
GLM-4.5
355.0Bparameters
3.0B
DeepSeek VL2 Tiny
355.0B
GLM-4.5

Context Window

Maximum input and output token capacity

Only GLM-4.5 specifies input context (131,072 tokens). Only GLM-4.5 specifies output context (131,072 tokens).

DeepSeek
DeepSeek VL2 Tiny
Input- tokens
Output- tokens
Zhipu AI
GLM-4.5
Input131,072 tokens
Output131,072 tokens
Mon Apr 20 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Tiny supports multimodal inputs, whereas GLM-4.5 does not.

DeepSeek VL2 Tiny can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek VL2 Tiny

Text
Images
Audio
Video

GLM-4.5

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while GLM-4.5 uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek VL2 Tiny

deepseek

Open weights

GLM-4.5

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while GLM-4.5 was released on 2025-07-28.

GLM-4.5 is 8 months newer than DeepSeek VL2 Tiny.

DeepSeek VL2 Tiny

Dec 13, 2024

1.4 years ago

GLM-4.5

Jul 28, 2025

8 months ago

7mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

DeepSeek
Supports multimodal inputs
Zhipu AI
Larger context window (131,072 tokens)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
Zhipu AI
GLM-4.5

FAQ

Common questions about DeepSeek VL2 Tiny vs GLM-4.5

DeepSeek VL2 Tiny (DeepSeek) and GLM-4.5 (Zhipu AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.
DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. GLM-4.5 scores MATH-500: 98.2%, AIME 2024: 91.0%, MMLU-Pro: 84.6%, TAU-bench Retail: 79.7%, GPQA: 79.1%.
DeepSeek VL2 Tiny supports an unknown number of tokens and GLM-4.5 supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (yes vs no), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.
DeepSeek VL2 Tiny is developed by DeepSeek and GLM-4.5 is developed by Zhipu AI.