Model Comparison

DeepSeek-V3.1 vs Qwen3 VL 32B InstructWhich is better in 2026?

DeepSeek-V3.1 shows notably better performance in the majority of benchmarks.

Verdict: DeepSeek-V3.1 vs Qwen3 VL 32B Instruct — which is better?

DeepSeek-V3.1 (by DeepSeek) and Qwen3 VL 32B 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.

DeepSeek-V3.1 outperforms in 3 benchmarks (GPQA, MMLU-Pro, MMLU-Redux), while Qwen3 VL 32B Instruct is better at 1 benchmark (AIME 2025). DeepSeek-V3.1 shows notably better performance in the majority of benchmarks.

Choose DeepSeek-V3.1 if…

  • you want the strongest raw capability — it leads on 3 of 4 shared benchmarks

Choose Qwen3 VL 32B Instruct if…

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

Performance Benchmarks

Comparative analysis across standard metrics

4 benchmarks

DeepSeek-V3.1 outperforms in 3 benchmarks (GPQA, MMLU-Pro, MMLU-Redux), while Qwen3 VL 32B Instruct is better at 1 benchmark (AIME 2025).

DeepSeek-V3.1 shows notably better performance in the majority of benchmarks.

Sat Jun 27 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

638.0B diff

DeepSeek-V3.1 has 638.0B more parameters than Qwen3 VL 32B Instruct, making it 1933.3% larger.

DeepSeek
DeepSeek-V3.1
671.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct
33.0Bparameters
671.0B
DeepSeek-V3.1
33.0B
Qwen3 VL 32B 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
Qwen3 VL 32B Instruct
Input- tokens
Output- tokens
Sat Jun 27 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 32B Instruct supports multimodal inputs, whereas DeepSeek-V3.1 does not.

Qwen3 VL 32B 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

Qwen3 VL 32B Instruct

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V3.1 is licensed under MIT, while Qwen3 VL 32B Instruct uses Apache 2.0.

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

DeepSeek-V3.1

MIT

Open weights

Qwen3 VL 32B Instruct

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3.1 was released on 2025-01-10, while Qwen3 VL 32B Instruct was released on 2025-09-22.

Qwen3 VL 32B Instruct is 9 months newer than DeepSeek-V3.1.

DeepSeek-V3.1

Jan 10, 2025

1.5 years ago

Qwen3 VL 32B Instruct

Sep 22, 2025

9 months ago

8mo 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)
Higher GPQA score (74.9% vs 68.9%)
Higher MMLU-Pro score (83.7% vs 78.6%)
Higher MMLU-Redux score (91.8% vs 89.8%)
Alibaba Cloud / Qwen Team

Qwen3 VL 32B Instruct

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs
Higher AIME 2025 score (66.2% vs 49.8%)

Detailed Comparison

Interactive Arena

Judge for yourself.

Run your own prompts against DeepSeek-V3.1 and Qwen3 VL 32B Instruct side-by-side, then vote on the output you prefer.

DeepSeek-V3.1
✓ Preferred
Qwen3 VL 32B Instruct
Open in Playground
AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V3.1
Alibaba Cloud / Qwen Team
Qwen3 VL 32B Instruct

FAQ

Common questions about DeepSeek-V3.1 vs Qwen3 VL 32B Instruct.

Which is better, DeepSeek-V3.1 or Qwen3 VL 32B Instruct?

DeepSeek-V3.1 shows notably better performance in the majority of benchmarks. DeepSeek-V3.1 is made by DeepSeek and Qwen3 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.

How does DeepSeek-V3.1 compare to Qwen3 VL 32B Instruct in benchmarks?

DeepSeek-V3.1 scores SimpleQA: 93.4%, MMLU-Redux: 91.8%, MMLU-Pro: 83.7%, GPQA: 74.9%, CodeForces: 69.7%. Qwen3 VL 32B Instruct scores DocVQAtest: 96.9%, ScreenSpot: 95.8%, CharXiv-D: 90.5%, MMLU-Redux: 89.8%, AI2D: 89.5%.

What are the context window sizes for DeepSeek-V3.1 and Qwen3 VL 32B Instruct?

DeepSeek-V3.1 supports 164K tokens and Qwen3 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.

What are the main differences between DeepSeek-V3.1 and Qwen3 VL 32B 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 Qwen3 VL 32B Instruct?

DeepSeek-V3.1 is developed by DeepSeek and Qwen3 VL 32B Instruct is developed by Alibaba Cloud / Qwen Team.