Model Comparison

DeepSeek VL2 Tiny vs Qwen2.5-Omni-7BWhich is better in 2026?

Qwen2.5-Omni-7B significantly outperforms across most benchmarks.

Verdict: DeepSeek VL2 Tiny vs Qwen2.5-Omni-7B — which is better?

DeepSeek VL2 Tiny (by DeepSeek) and Qwen2.5-Omni-7B (by Alibaba Cloud / Qwen Team) 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.

DeepSeek VL2 Tiny outperforms in 0 benchmarks, while Qwen2.5-Omni-7B is better at 9 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMBench-V1.1, MMMU, MMStar, RealWorldQA, TextVQA). Qwen2.5-Omni-7B significantly outperforms across most benchmarks.

Choose DeepSeek VL2 Tiny if…

  • you are already invested in the DeepSeek ecosystem

Choose Qwen2.5-Omni-7B if…

  • you want the strongest raw capability — it leads on 9 of 9 shared benchmarks
  • you want the most recent training data — it shipped Mar 2025

Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

DeepSeek VL2 Tiny outperforms in 0 benchmarks, while Qwen2.5-Omni-7B is better at 9 benchmarks (AI2D, ChartQA, DocVQA, MathVista, MMBench-V1.1, MMMU, MMStar, RealWorldQA, TextVQA).

Qwen2.5-Omni-7B significantly outperforms across most benchmarks.

Fri Jun 12 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

4.0B diff

Qwen2.5-Omni-7B has 4.0B more parameters than DeepSeek VL2 Tiny, making it 133.3% larger.

DeepSeek
DeepSeek VL2 Tiny
3.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
3.0B
DeepSeek VL2 Tiny
7.0B
Qwen2.5-Omni-7B

Input Capabilities

Supported data types and modalities

Both DeepSeek VL2 Tiny and Qwen2.5-Omni-7B support multimodal inputs.

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

DeepSeek VL2 Tiny

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Tiny is licensed under deepseek, while Qwen2.5-Omni-7B uses Apache 2.0.

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

DeepSeek VL2 Tiny

deepseek

Open weights

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Tiny was released on 2024-12-13, while Qwen2.5-Omni-7B was released on 2025-03-27.

Qwen2.5-Omni-7B is 3 months newer than DeepSeek VL2 Tiny.

DeepSeek VL2 Tiny

Dec 13, 2024

1.5 years ago

Qwen2.5-Omni-7B

Mar 27, 2025

1.2 years ago

3mo 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

Notice missing or incorrect data?Start an Issue discussion

Key Takeaways

No standout differentiators in the data we have for this pair.

Alibaba Cloud / Qwen Team

Qwen2.5-Omni-7B

View details

Alibaba Cloud / Qwen Team

Higher AI2D score (83.2% vs 71.6%)
Higher ChartQA score (85.3% vs 81.0%)
Higher DocVQA score (95.2% vs 88.9%)
Higher MathVista score (67.9% vs 53.6%)
Higher MMBench-V1.1 score (81.8% vs 68.3%)
Higher MMMU score (59.2% vs 40.7%)
Higher MMStar score (64.0% vs 45.9%)
Higher RealWorldQA score (70.3% vs 64.2%)
Higher TextVQA score (84.4% vs 80.7%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek VL2 Tiny
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B

FAQ

Common questions about DeepSeek VL2 Tiny vs Qwen2.5-Omni-7B.

Which is better, DeepSeek VL2 Tiny or Qwen2.5-Omni-7B?

Qwen2.5-Omni-7B significantly outperforms across most benchmarks. DeepSeek VL2 Tiny is made by DeepSeek and Qwen2.5-Omni-7B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek VL2 Tiny compare to Qwen2.5-Omni-7B in benchmarks?

DeepSeek VL2 Tiny scores DocVQA: 88.9%, ChartQA: 81.0%, OCRBench: 80.9%, TextVQA: 80.7%, AI2D: 71.6%. Qwen2.5-Omni-7B scores FLEURS: 95.9%, DocVQA: 95.2%, VocalSound: 93.9%, GSM8k: 88.7%, GiantSteps Tempo: 88.0%.

What are the main differences between DeepSeek VL2 Tiny and Qwen2.5-Omni-7B?

Key differences include licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek VL2 Tiny and Qwen2.5-Omni-7B?

DeepSeek VL2 Tiny is developed by DeepSeek and Qwen2.5-Omni-7B is developed by Alibaba Cloud / Qwen Team.