Model Comparison

DeepSeek-V3 vs Qwen3 VL 30B A3B Thinking

Both models are evenly matched across the benchmarks. Qwen3 VL 30B A3B Thinking is 1.2x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

6 benchmarks

DeepSeek-V3 outperforms in 3 benchmarks (IFEval, MMLU, SimpleQA), while Qwen3 VL 30B A3B Thinking is better at 3 benchmarks (GPQA, MMLU-Pro, MMLU-Redux).

Both models are evenly matched across the benchmarks.

Sun May 31 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3 VL 30B A3B Thinking costs less

For input processing, DeepSeek-V3 ($0.27/1M tokens) is 1.4x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).

For output processing, DeepSeek-V3 ($1.10/1M tokens) is 1.1x more expensive than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).

In conclusion, DeepSeek-V3 is more expensive than Qwen3 VL 30B A3B Thinking.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Sun May 31 2026 • llm-stats.com

DeepSeek-V3

Input tokens$0.27

Output tokens$1.10

Best providerDeepSeek

Qwen3 VL 30B A3B Thinking

Input tokens$0.20

Output tokens$0.99

Best providerNovita

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Model Size

Parameter count comparison

640.0B diff

DeepSeek-V3 has 640.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 2064.5% larger.

DeepSeek-V3

671.0Bparameters

Qwen3 VL 30B A3B Thinking

31.0Bparameters

671.0B

DeepSeek-V3

31.0B

Qwen3 VL 30B A3B Thinking

Context Window

Maximum input and output token capacity

Both models have the same input context window of 131,072 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.

DeepSeek-V3

Input131,072 tokens

Output131,072 tokens

Qwen3 VL 30B A3B Thinking

Input131,072 tokens

Output32,768 tokens

Sun May 31 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas DeepSeek-V3 does not.

Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V3

Text

Images

Audio

Video

Qwen3 VL 30B A3B Thinking

Text

Images

Audio

Video

License

Usage and distribution terms

DeepSeek-V3 is licensed under MIT + Model License (Commercial use allowed), while Qwen3 VL 30B A3B Thinking 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

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V3 was released on 2024-12-25, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.

Qwen3 VL 30B A3B Thinking is 9 months newer than DeepSeek-V3.

DeepSeek-V3

Dec 25, 2024

1.4 years ago

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

8 months ago

9mo 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

Provider Availability

DeepSeek-V3 is available from DeepSeek. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.

DeepSeek-V3

DeepSeek

Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M

Qwen3 VL 30B A3B Thinking

Novita

Input Price:Input: $0.20/1MOutput Price:Output: $1.00/1M

Deepinfra

Input Price:Input: $0.29/1MOutput Price:Output: $0.99/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

DeepSeek-V3

View details

DeepSeek

Higher IFEval score (86.1% vs 81.7%)

Higher MMLU score (88.5% vs 87.6%)

Higher SimpleQA score (24.9% vs 23.9%)

Qwen3 VL 30B A3B Thinking

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Less expensive input tokens

Less expensive output tokens

Higher GPQA score (74.4% vs 59.1%)

Higher MMLU-Pro score (80.5% vs 75.9%)

Higher MMLU-Redux score (90.9% vs 89.1%)

Detailed Comparison

AI Model Comparison Table
Feature	DeepSeek-V3	Qwen3 VL 30B A3B Thinking

FAQ

Common questions about DeepSeek-V3 vs Qwen3 VL 30B A3B Thinking.

Which is better, DeepSeek-V3 or Qwen3 VL 30B A3B Thinking?

Both models are evenly matched across the benchmarks. DeepSeek-V3 is made by DeepSeek and Qwen3 VL 30B A3B Thinking 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 compare to Qwen3 VL 30B A3B Thinking in benchmarks?

DeepSeek-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%. Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%.

Is DeepSeek-V3 cheaper than Qwen3 VL 30B A3B Thinking?

Qwen3 VL 30B A3B Thinking is 1.4x cheaper for input tokens. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek. Qwen3 VL 30B A3B Thinking costs $0.20/M input and $0.99/M output via novita.

What are the context window sizes for DeepSeek-V3 and Qwen3 VL 30B A3B Thinking?

DeepSeek-V3 supports 131K tokens and Qwen3 VL 30B A3B Thinking supports 131K 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 and Qwen3 VL 30B A3B Thinking?

Key differences include input pricing ($0.27 vs $0.20/M), 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.

Who makes DeepSeek-V3 and Qwen3 VL 30B A3B Thinking?

DeepSeek-V3 is developed by DeepSeek and Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team.