Model Comparison

DeepSeek-V3.1 vs Qwen2.5 VL 7B InstructWhich is better in 2026?

Comparing DeepSeek-V3.1 and Qwen2.5 VL 7B Instruct across benchmarks, pricing, and capabilities.

Verdict: DeepSeek-V3.1 vs Qwen2.5 VL 7B Instruct — which is better?

DeepSeek-V3.1 (by DeepSeek) and Qwen2.5 VL 7B Instruct (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.

Choose DeepSeek-V3.1 if…

  • you want predictable pricing at $0.27/M input and $1.00/M output

Choose Qwen2.5 VL 7B Instruct if…

  • you want the most recent training data — it shipped Jan 2025

Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

DeepSeek-V3.1 and Qwen2.5 VL 7B Instruct 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

662.7B diff

DeepSeek-V3.1 has 662.7B more parameters than Qwen2.5 VL 7B Instruct, making it 7994.1% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 7B Instruct
8.3Bparameters
671.0B
DeepSeek-V3.1
8.3B
Qwen2.5 VL 7B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3.1 specifies input context (163,840 tokens). Only DeepSeek-V3.1 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3.1
Input163,840 tokens
Output163,840 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 7B Instruct
Input- tokens
Output- tokens
Sun Jun 07 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 7B Instruct supports multimodal inputs, whereas DeepSeek-V3.1 does not.

Qwen2.5 VL 7B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3.1

Text
Images
Audio
Video

Qwen2.5 VL 7B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Qwen2.5 VL 7B Instruct uses Apache 2.0.

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

DeepSeek-V3.1

MIT

Open weights

Qwen2.5 VL 7B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Qwen2.5 VL 7B Instruct was released on 2025-01-26.

Qwen2.5 VL 7B Instruct is 1 month newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.4 years ago

Qwen2.5 VL 7B Instruct

Jan 26, 2025

1.4 years ago

2w 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

Larger context window (163,840 tokens)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 7B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Alibaba Cloud / Qwen Team
Qwen2.5 VL 7B Instruct

FAQ

Common questions about DeepSeek-V3.1 vs Qwen2.5 VL 7B Instruct.

Which is better, DeepSeek-V3.1 or Qwen2.5 VL 7B Instruct?

DeepSeek-V3.1 (DeepSeek) and Qwen2.5 VL 7B Instruct (Alibaba Cloud / Qwen Team) 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-V3.1 compare to Qwen2.5 VL 7B Instruct in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Qwen2.5 VL 7B Instruct scores DocVQA: 95.7%, Android Control Low_EM: 91.4%, MobileMiniWob++_SR: 91.4%, ChartQA: 87.3%, OCRBench: 86.4%.

What are the context window sizes for DeepSeek-V3.1 and Qwen2.5 VL 7B Instruct?

DeepSeek-V3.1 supports 164K tokens and Qwen2.5 VL 7B Instruct 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 DeepSeek-V3.1 and Qwen2.5 VL 7B Instruct?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V3.1 and Qwen2.5 VL 7B Instruct?

DeepSeek-V3.1 is developed by DeepSeek and Qwen2.5 VL 7B Instruct is developed by Alibaba Cloud / Qwen Team.