DeepSeek R1 Distill Qwen 7B vs Qwen3 VL 32B Instruct
Qwen3 VL 32B Instruct leads the LLM Stats Score 20.4 to 8.5.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 32B Instruct leads the overall LLM Stats Score 20.4 to 8.5, ranking #185 overall.
In the 1 individual benchmarks reported for both models, Qwen3 VL 32B Instruct wins 1; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Qwen 7B
- you are already invested in the DeepSeek ecosystem
Choose Qwen3 VL 32B Instruct
- overall performance matters — it scores 20.4 and ranks #185 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- 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
4 reported for DeepSeek R1 Distill Qwen 7B · 45 for Qwen3 VL 32B Instruct
DeepSeek R1 Distill Qwen 7B outperforms in 0 benchmarks, while Qwen3 VL 32B Instruct is better at 1 benchmark (GPQA).
Qwen3 VL 32B Instruct significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3 VL 32B Instruct has 25.4B more parameters than DeepSeek R1 Distill Qwen 7B, making it 333.1% larger.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 32B Instruct supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 7B does not.
Qwen3 VL 32B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 7B
Qwen3 VL 32B Instruct
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 7B 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.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek R1 Distill Qwen 7B was released on 2025-01-20, while Qwen3 VL 32B Instruct was released on 2025-09-22.
Qwen3 VL 32B Instruct is 8 months newer than DeepSeek R1 Distill Qwen 7B.
Jan 20, 2025
1.6 years ago
Sep 22, 2025
11 months ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Qwen 7B and Qwen3 VL 32B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 7B vs Qwen3 VL 32B Instruct.