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DeepSeek VL2 Small vs Qwen2.5-Omni-7B

DeepSeek VL2 Small and Qwen2.5-Omni-7B are closely matched at 1.4 and 5.3 on the LLM Stats Score.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek VL2 Small and Qwen2.5-Omni-7B are closely matched on the overall LLM Stats Score at 1.4 and 5.3.

In the 9 individual benchmarks reported for both models, Qwen2.5-Omni-7B wins 9; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek VL2 Small

  • you are already invested in the DeepSeek ecosystem

Choose Qwen2.5-Omni-7B

  • you value its reported benchmark strengths — it wins 9 of 9 exact shared results
  • you want the most recent training data — it shipped Mar 2025

At a glance

The differences that matter most.

Core performance indexes
1.4
#309
5.3
#286
-3.6
#326
1.6
#298
Cost, coverage & limits
Benchmark wins
0 of 9
9 of 9
Input price
— / M
— / M
Output price
— / M
— / M
Context window

Capability indexes

Additional strengths measured across groups of related public benchmarks

2 shared
Index
DeepSeek VL2 Small
Qwen2.5-Omni-7B
1.1#174
5.8#149
3.8#138
7.3#126
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

14 reported for DeepSeek VL2 Small · 45 for Qwen2.5-Omni-7B

9 shared

DeepSeek VL2 Small 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 Sep 04 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

9.0B diff

DeepSeek VL2 Small has 9.0B more parameters than Qwen2.5-Omni-7B, making it 128.6% larger.

DeepSeek
DeepSeek VL2 Small
16.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B
7.0Bparameters
16.0B
DeepSeek VL2 Small
7.0B
Qwen2.5-Omni-7B

Input capabilities

Documented input modalities across available providers

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

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

DeepSeek VL2 Small

Text
Images
Audio
Video

Qwen2.5-Omni-7B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek VL2 Small 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 Small

deepseek

Open weights

Qwen2.5-Omni-7B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek VL2 Small 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 Small.

DeepSeek VL2 Small

Dec 13, 2024

1.7 years ago

Qwen2.5-Omni-7B

Mar 27, 2025

1.4 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

Judge for yourself.

Run your own prompts against DeepSeek VL2 Small and Qwen2.5-Omni-7B side-by-side, then vote on the output you prefer.

DeepSeek VL2 Small
✓ Preferred
Qwen2.5-Omni-7B
Open in Playground

FAQ

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

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

DeepSeek VL2 Small and Qwen2.5-Omni-7B are closely matched on the LLM Stats Score at 1.4 and 5.3. DeepSeek VL2 Small 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 capability indexes, individual benchmarks, pricing, and limits above.

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

DeepSeek VL2 Small scores DocVQA: 92.3%, ChartQA: 84.5%, OCRBench: 83.4%, TextVQA: 83.4%, MMBench: 80.3%. 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 Small and Qwen2.5-Omni-7B?

Key differences include LLM Stats Score (1.4 vs 5.3), licensing (deepseek vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

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

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