Model Comparison

GLM-5 vs DeepSeek VL2Which is better in 2026?

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

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

GLM-5 (by Zhipu AI) and DeepSeek VL2 (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.

GLM-5 also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.

Choose GLM-5 if…

  • you process long inputs — it offers a 200,000 token context window
  • you want the most recent training data — it shipped Feb 2026

Choose DeepSeek VL2 if…

  • you are already invested in the DeepSeek ecosystem

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GLM-5 and DeepSeek VL2 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

717.0B diff

GLM-5 has 717.0B more parameters than DeepSeek VL2, making it 2655.6% larger.

Zhipu AI
GLM-5
744.0Bparameters
DeepSeek
DeepSeek VL2
27.0Bparameters
744.0B
GLM-5
27.0B
DeepSeek VL2

Context Window

Maximum input and output token capacity

GLM-5 accepts 200,000 input tokens compared to DeepSeek VL2's 129,280 tokens. DeepSeek VL2 can generate longer responses up to 129,280 tokens, while GLM-5 is limited to 128,000 tokens.

Zhipu AI
GLM-5
Input200,000 tokens
Output128,000 tokens
DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Sun Jun 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

DeepSeek VL2 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

Text
Images
Audio
Video

License

Usage and distribution terms

GLM-5 is licensed under MIT, while DeepSeek VL2 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

deepseek

Open weights

Release Timeline

When each model was launched

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

GLM-5 is 14 months newer than DeepSeek VL2.

GLM-5

Feb 11, 2026

3 months ago

1.2yr newer
DeepSeek VL2

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

Provider Availability

GLM-5 is available from FriendliAI, ZAI. DeepSeek VL2 is available from Replicate.

GLM-5

friendli logo
FriendliAI
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M
z logo
Unknown Organization
Input Price:Input: $1.00/1MOutput Price:Output: $3.20/1M

DeepSeek VL2

replicate logo
Replicate
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

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

Detailed Comparison

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

FAQ

Common questions about GLM-5 vs DeepSeek VL2.

Which is better, GLM-5 or DeepSeek VL2?

GLM-5 (Zhipu AI) and DeepSeek VL2 (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 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 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%.

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

GLM-5 supports 200K tokens and DeepSeek VL2 supports 129K 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?

Key differences include context window (200K vs 129K), 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?

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