Model Comparison

DeepSeek-V3 vs Qwen2.5 VL 32B Instruct

DeepSeek-V3 significantly outperforms across most benchmarks.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V3 outperforms in 3 benchmarks (GPQA, MMLU, MMLU-Pro), while Qwen2.5 VL 32B Instruct is better at 0 benchmarks.

DeepSeek-V3 significantly outperforms across most benchmarks.

Thu Apr 30 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Thu Apr 30 2026 • llm-stats.com
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

637.5B diff

DeepSeek-V3 has 637.5B more parameters than Qwen2.5 VL 32B Instruct, making it 1903.0% larger.

DeepSeek
DeepSeek-V3
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
33.5Bparameters
671.0B
DeepSeek-V3
33.5B
Qwen2.5 VL 32B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 specifies input context (131,072 tokens). Only DeepSeek-V3 specifies output context (131,072 tokens).

DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
Input- tokens
Output- tokens
Thu Apr 30 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas DeepSeek-V3 does not.

Qwen2.5 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3

Text
Images
Audio
Video

Qwen2.5 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Qwen2.5 VL 32B Instruct uses Apache 2.0.

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

DeepSeek-V3

MIT + Model License (Commercial use allowed)

Open weights

Qwen2.5 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.

Qwen2.5 VL 32B Instruct is 2 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.3 years ago

Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.2 years ago

2mo 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

DeepSeek
Larger context window (131,072 tokens)
Higher GPQA score (59.1% vs 46.0%)
Higher MMLU score (88.5% vs 78.4%)
Higher MMLU-Pro score (75.9% vs 68.8%)
Alibaba Cloud / Qwen Team

Qwen2.5 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct

FAQ

Common questions about DeepSeek-V3 vs Qwen2.5 VL 32B Instruct

DeepSeek-V3 significantly outperforms across most benchmarks. DeepSeek-V3 is made by DeepSeek and Qwen2.5 VL 32B Instruct is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Qwen2.5 VL 32B Instruct scores DocVQA: 94.8%, Android Control Low_EM: 93.3%, HumanEval: 91.5%, ScreenSpot: 88.5%, MBPP: 84.0%.
DeepSeek-V3 supports 131K tokens and Qwen2.5 VL 32B Instruct supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include multimodal support (no vs yes), licensing (MIT + Model License (Commercial use allowed) vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.
DeepSeek-V3 is developed by DeepSeek and Qwen2.5 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.