DeepSeek R1 Distill Llama 8B vs Qwen3 VL 4B Thinking
DeepSeek R1 Distill Llama 8B and Qwen3 VL 4B Thinking are closely matched at 7.0 and 12.9 on the LLM Stats Score.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek R1 Distill Llama 8B and Qwen3 VL 4B Thinking are closely matched on the overall LLM Stats Score at 7.0 and 12.9.
In the 1 individual benchmarks reported for both models, Qwen3 VL 4B Thinking 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 Llama 8B
- you are already invested in the DeepSeek ecosystem
Choose Qwen3 VL 4B Thinking
- 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 Llama 8B · 48 for Qwen3 VL 4B Thinking
DeepSeek R1 Distill Llama 8B outperforms in 0 benchmarks, while Qwen3 VL 4B Thinking is better at 1 benchmark (GPQA).
Qwen3 VL 4B Thinking significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek R1 Distill Llama 8B has 4.0B more parameters than Qwen3 VL 4B Thinking, making it 100.8% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 4B Thinking specifies input context (262,144 tokens). Only Qwen3 VL 4B Thinking specifies output context (262,144 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3 VL 4B Thinking supports multimodal inputs, whereas DeepSeek R1 Distill Llama 8B does not.
Qwen3 VL 4B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek R1 Distill Llama 8B
Qwen3 VL 4B Thinking
License
Usage and distribution terms
DeepSeek R1 Distill Llama 8B is licensed under MIT, while Qwen3 VL 4B Thinking 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 Llama 8B was released on 2025-01-20, while Qwen3 VL 4B Thinking was released on 2025-09-22.
Qwen3 VL 4B Thinking is 8 months newer than DeepSeek R1 Distill Llama 8B.
Jan 20, 2025
1.7 years ago
Sep 22, 2025
12 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 Llama 8B and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Llama 8B vs Qwen3 VL 4B Thinking.