Model Comparison

GLM-5 vs DeepSeek VL2 SmallWhich is better in 2026?

Comparing GLM-5 and DeepSeek VL2 Small across benchmarks, pricing, and capabilities.

Verdict: GLM-5 vs DeepSeek VL2 Small — which is better?

GLM-5 (by Zhipu AI) and DeepSeek VL2 Small (by DeepSeek) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

Choose GLM-5 if…

  • you want the most recent training data — it shipped Feb 2026

Choose DeepSeek VL2 Small if…

  • you are already invested in the DeepSeek ecosystem
Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and DeepSeek VL2 Small don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Model Size

Parameter count comparison

728.0B diff

GLM-5 has 728.0B more parameters than DeepSeek VL2 Small, making it 4550.0% larger.

Zhipu AI
GLM-5
744.0Bparameters
DeepSeek
DeepSeek VL2 Small
16.0Bparameters
744.0B
GLM-5
16.0B
DeepSeek VL2 Small

Context Window

Maximum input and output token capacity

Only GLM-5 specifies input context (200,000 tokens). Only GLM-5 specifies output context (128,000 tokens).

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek VL2 Small
Input- tokens
Output- tokens
Sat Jun 06 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

DeepSeek VL2 Small supports multimodal inputs, whereas GLM-5 does not.

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

GLM-5

Text
Images
Audio
Video

DeepSeek VL2 Small

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while DeepSeek VL2 Small uses deepseek.

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

GLM-5

MIT

Open weights

DeepSeek VL2 Small

deepseek

Open weights

Release Timeline

When each model was launched

GLM-5 was released on 2026-02-11, while DeepSeek VL2 Small was released on 2024-12-13.

GLM-5 is 14 months newer than DeepSeek VL2 Small.

GLM-5

Feb 11, 2026

3 months ago

1.2yr newer
DeepSeek VL2 Small

Dec 13, 2024

1.5 years ago

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

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Zhipu AI
Larger context window (200,000 tokens)
DeepSeek
Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
Zhipu AI
GLM-5
DeepSeek
DeepSeek VL2 Small

FAQ

Common questions about GLM-5 vs DeepSeek VL2 Small.

Which is better, GLM-5 or DeepSeek VL2 Small?

GLM-5 (Zhipu AI) and DeepSeek VL2 Small (DeepSeek) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GLM-5 compare to DeepSeek VL2 Small in benchmarks?

GLM-5 scores t2-bench: 89.7%, SWE-Bench Verified: 77.8%, BrowseComp: 75.9%, MCP Atlas: 67.8%, Terminal-Bench 2.0: 56.2%. DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%.

What are the context window sizes for GLM-5 and DeepSeek VL2 Small?

GLM-5 supports 200K tokens and DeepSeek VL2 Small supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GLM-5 and DeepSeek VL2 Small?

Key differences include multimodal support (no vs yes), licensing (MIT vs deepseek). See the full comparison above for benchmark-by-benchmark results.

Who makes GLM-5 and DeepSeek VL2 Small?

GLM-5 is developed by Zhipu AI and DeepSeek VL2 Small is developed by DeepSeek.

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