DeepSeek R1 Distill Qwen 1.5B vs Qwen3 VL 4B Instruct
Qwen3 VL 4B Instruct leads the LLM Stats Score 10.8 to -2.8.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 VL 4B Instruct leads the overall LLM Stats Score 10.8 to -2.8, ranking #252 overall.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Qwen 1.5B
- you are already invested in the DeepSeek ecosystem
Choose Qwen3 VL 4B Instruct
- overall performance matters — it scores 10.8 and ranks #252 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- 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 1.5B · 45 for Qwen3 VL 4B Instruct
DeepSeek R1 Distill Qwen 1.5B and Qwen3 VL 4B Instructdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3 VL 4B Instruct has 2.2B more parameters than DeepSeek R1 Distill Qwen 1.5B, making it 124.7% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 4B Instruct specifies input context (262,144 tokens). Only Qwen3 VL 4B Instruct specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3 VL 4B Instruct supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 1.5B does not.
Qwen3 VL 4B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Qwen 1.5B
Qwen3 VL 4B Instruct
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 1.5B is licensed under MIT, while Qwen3 VL 4B 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 1.5B was released on 2025-01-20, while Qwen3 VL 4B Instruct was released on 2025-09-22.
Qwen3 VL 4B Instruct is 8 months newer than DeepSeek R1 Distill Qwen 1.5B.
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 1.5B and Qwen3 VL 4B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Qwen 1.5B vs Qwen3 VL 4B Instruct.