Model Comparison

DeepSeek-V3 0324 vs Qwen2.5 VL 32B Instruct

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

DeepSeek-V3 0324 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while Qwen2.5 VL 32B Instruct is better at 0 benchmarks.

DeepSeek-V3 0324 significantly outperforms across most benchmarks.

Fri May 01 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
Fri May 01 2026 • llm-stats.com
DeepSeek
DeepSeek-V3 0324
Input tokens$0.28
Output tokens$1.14
Best providerNovita
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 0324 has 637.5B more parameters than Qwen2.5 VL 32B Instruct, making it 1903.0% larger.

DeepSeek
DeepSeek-V3 0324
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
33.5Bparameters
671.0B
DeepSeek-V3 0324
33.5B
Qwen2.5 VL 32B Instruct

Context Window

Maximum input and output token capacity

Only DeepSeek-V3 0324 specifies input context (163,840 tokens). Only DeepSeek-V3 0324 specifies output context (163,840 tokens).

DeepSeek
DeepSeek-V3 0324
Input163,840 tokens
Output163,840 tokens
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct
Input- tokens
Output- tokens
Fri May 01 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen2.5 VL 32B Instruct supports multimodal inputs, whereas DeepSeek-V3 0324 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 0324

Text
Images
Audio
Video

Qwen2.5 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3 0324 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 0324

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 0324 was released on 2025-03-25, while Qwen2.5 VL 32B Instruct was released on 2025-02-28.

DeepSeek-V3 0324 is 1 month newer than Qwen2.5 VL 32B Instruct.

DeepSeek-V3 0324

Mar 25, 2025

1.1 years ago

3w newer
Qwen2.5 VL 32B Instruct

Feb 28, 2025

1.2 years ago

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)
Higher GPQA score (68.4% vs 46.0%)
Higher MMLU-Pro score (81.2% 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 0324
Alibaba Cloud / Qwen Team
Qwen2.5 VL 32B Instruct

FAQ

Common questions about DeepSeek-V3 0324 vs Qwen2.5 VL 32B Instruct

DeepSeek-V3 0324 significantly outperforms across most benchmarks. DeepSeek-V3 0324 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 0324 scores MATH-500: 94.0%, MMLU-Pro: 81.2%, GPQA: 68.4%, AIME 2024: 59.4%, LiveCodeBench: 49.2%. 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 0324 supports 164K 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 0324 is developed by DeepSeek and Qwen2.5 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.