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DeepSeek VL2 vs GLM-5.3-Flash

Comparing DeepSeek VL2 and GLM-5.3-Flash across benchmarks, pricing, and capabilities.

DeepSeek · Zhipu AI · Updated for 2026

Which is better?

DeepSeek VL2 and GLM-5.3-Flash trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.

GLM-5.3-Flash also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek VL2

  • you are already invested in the DeepSeek ecosystem

Choose GLM-5.3-Flash

  • you process long inputs — it offers a 1,000,000 token context window
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

DeepSeek VL2
DeepSeek
GLM-5.3-Flash
Zhipu AI
Benchmark wins
—
—
Input price
— / M
$0.15 / M
Output price
— / M
$0.50 / M
Context window
129,280
1,000,000
Released
Dec 2024
Aug 2026
License
deepseek
MIT

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek VL2 and GLM-5.3-Flashdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

293.0B diff

GLM-5.3-Flash has 293.0B more parameters than DeepSeek VL2, making it 1085.2% larger.

DeepSeek
DeepSeek VL2
27.0Bparameters
Zhipu AI
GLM-5.3-Flash
320.0Bparameters
27.0B
DeepSeek VL2
320.0B
GLM-5.3-Flash

Context Window

Maximum input and output token capacity

GLM-5.3-Flash accepts 1,000,000 input tokens compared to DeepSeek VL2's 129,280 tokens. GLM-5.3-Flash can generate longer responses up to 131,072 tokens, while DeepSeek VL2 is limited to 129,280 tokens.

DeepSeek
DeepSeek VL2
Input129,280 tokens
Output129,280 tokens
Zhipu AI
GLM-5.3-Flash
Input1,000,000 tokens
Output131,072 tokens
Wed Aug 26 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 and GLM-5.3-Flash support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek VL2

Text
Images
Audio
Video

GLM-5.3-Flash

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 is licensed under deepseek, while GLM-5.3-Flash uses MIT.

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

DeepSeek VL2

deepseek

Open weights

GLM-5.3-Flash

MIT

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 was released on 2024-12-13, while GLM-5.3-Flash was released on 2026-08-26.

GLM-5.3-Flash is 21 months newer than DeepSeek VL2.

DeepSeek VL2

Dec 13, 2024

1.7 years ago

GLM-5.3-Flash

Aug 26, 2026

0 days ago

1.7yr 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

Provider Availability

DeepSeek VL2 is available from Replicate. GLM-5.3-Flash is available from ZAI.

DeepSeek VL2

replicate logo
Replicate

GLM-5.3-Flash

z logo
Unknown Organization
Input Price:Input: $0.15/1MOutput Price:Output: $0.50/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek VL2 and GLM-5.3-Flash side-by-side, then vote on the output you prefer.

DeepSeek VL2
✓ Preferred
GLM-5.3-Flash
Open in Playground

FAQ

Common questions about DeepSeek VL2 vs GLM-5.3-Flash.

Which is better, DeepSeek VL2 or GLM-5.3-Flash?

DeepSeek VL2 (DeepSeek) and GLM-5.3-Flash (Zhipu AI) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does DeepSeek VL2 compare to GLM-5.3-Flash in benchmarks?

DeepSeek VL2 scores DocVQA: 93.3%, ChartQA: 86.0%, TextVQA: 84.2%, AI2D: 81.4%, OCRBench: 81.1%. GLM-5.3-Flash scores CharXiv-R: 89.4%, Terminal-Bench 2.1: 84.3%, MMVU: 80.5%, Toolathlon: 78.4%, MVBench: 77.8%.

What are the context window sizes for DeepSeek VL2 and GLM-5.3-Flash?

DeepSeek VL2 supports 129K tokens and GLM-5.3-Flash supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek VL2 and GLM-5.3-Flash?

Key differences include context window (129K vs 1.0M), licensing (deepseek vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 and GLM-5.3-Flash?

DeepSeek VL2 is developed by DeepSeek and GLM-5.3-Flash is developed by Zhipu AI.

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