DeepSeek-V3 0324 vs Qwen3 VL 30B A3B Thinking
DeepSeek-V3 0324 and Qwen3 VL 30B A3B Thinking are closely matched at 13.4 and 18.3 on the LLM Stats Score. Qwen3 VL 30B A3B Thinking is 1.0x cheaper per token.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V3 0324 and Qwen3 VL 30B A3B Thinking are closely matched on the overall LLM Stats Score at 13.4 and 18.3.
The models split the 2 individual benchmarks reported for both models evenly.
DeepSeek-V3 0324 also accepts a larger context window (163,840 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V3 0324
- you process long inputs — it offers a 163,840 token context window
Choose Qwen3 VL 30B A3B Thinking
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
5 reported for DeepSeek-V3 0324 · 50 for Qwen3 VL 30B A3B Thinking
DeepSeek-V3 0324 outperforms in 1 benchmarks (MMLU-Pro), while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (GPQA).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V3 0324 ($0.24/1M tokens) is 1.2x more expensive than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, DeepSeek-V3 0324 ($0.90/1M tokens) is 1.1x cheaper than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, DeepSeek-V3 0324 is more expensive than Qwen3 VL 30B A3B Thinking.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-V3 0324 has 640.0B more parameters than Qwen3 VL 30B A3B Thinking, making it 2064.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V3 0324 accepts 163,840 input tokens compared to Qwen3 VL 30B A3B Thinking's 131,072 tokens. DeepSeek-V3 0324 can generate longer responses up to 163,840 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas DeepSeek-V3 0324 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 0324
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
DeepSeek-V3 0324 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.
MIT + Model License (Commercial use allowed)
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V3 0324 was released on 2025-03-25, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Qwen3 VL 30B A3B Thinking is 6 months newer than DeepSeek-V3 0324.
Mar 25, 2025
1.5 years ago
Sep 22, 2025
12 months ago
6mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V3 0324 is available from DeepInfra, Novita. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
DeepSeek-V3 0324
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V3 0324 and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V3 0324 vs Qwen3 VL 30B A3B Thinking.