Model Comparison
Llama 4 Scout vs Qwen3 VL 4B ThinkingWhich is better in 2026?
Qwen3 VL 4B Thinking shows notably better performance in the majority of benchmarks. Llama 4 Scout is 2.4x cheaper per token.
Verdict: Llama 4 Scout vs Qwen3 VL 4B Thinking — which is better?
Llama 4 Scout (by Meta) and Qwen3 VL 4B Thinking (by Alibaba Cloud / Qwen Team) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Llama 4 Scout outperforms in 1 benchmarks (MMLU-Pro), while Qwen3 VL 4B Thinking is better at 2 benchmarks (GPQA, MMLU). Qwen3 VL 4B Thinking shows notably better performance in the majority of benchmarks.
On price, Llama 4 Scout is roughly 2.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Llama 4 Scout also accepts a larger context window (10,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Choose Llama 4 Scout if…
- cost matters — it's about 2.4x cheaper per token
- you process long inputs — it offers a 10,000,000 token context window
Choose Qwen3 VL 4B Thinking if…
- you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
- you want the most recent training data — it shipped Sep 2025
Performance Benchmarks
Comparative analysis across standard metrics
Llama 4 Scout outperforms in 1 benchmarks (MMLU-Pro), while Qwen3 VL 4B Thinking is better at 2 benchmarks (GPQA, MMLU).
Qwen3 VL 4B Thinking shows notably better performance in the majority of benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Llama 4 Scout ($0.08/1M tokens) is 1.3x cheaper than Qwen3 VL 4B Thinking ($0.10/1M tokens).
For output processing, Llama 4 Scout ($0.30/1M tokens) is 3.3x cheaper than Qwen3 VL 4B Thinking ($1.00/1M tokens).
In conclusion, Qwen3 VL 4B Thinking is more expensive than Llama 4 Scout.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Llama 4 Scout has 105.0B more parameters than Qwen3 VL 4B Thinking, making it 2625.0% larger.
Context Window
Maximum input and output token capacity
Llama 4 Scout accepts 10,000,000 input tokens compared to Qwen3 VL 4B Thinking's 262,144 tokens. Llama 4 Scout can generate longer responses up to 10,000,000 tokens, while Qwen3 VL 4B Thinking is limited to 262,144 tokens.
Input Capabilities
Supported data types and modalities
Both Llama 4 Scout and Qwen3 VL 4B Thinking support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Llama 4 Scout
Qwen3 VL 4B Thinking
License
Usage and distribution terms
Llama 4 Scout is licensed under Llama 4 Community License Agreement, 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.
Llama 4 Community License Agreement
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Llama 4 Scout was released on 2025-04-05, while Qwen3 VL 4B Thinking was released on 2025-09-22.
Qwen3 VL 4B Thinking is 6 months newer than Llama 4 Scout.
Apr 5, 2025
1.3 years ago
Sep 22, 2025
10 months ago
5mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Llama 4 Scout is available from DeepInfra, Lambda, Novita, Groq, Fireworks, Together. Qwen3 VL 4B Thinking is available from DeepInfra.
Llama 4 Scout
Qwen3 VL 4B Thinking
Outputs Comparison
Key Takeaways
Qwen3 VL 4B Thinking
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against Llama 4 Scout and Qwen3 VL 4B Thinking side-by-side, then vote on the output you prefer.
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FAQ
Common questions about Llama 4 Scout vs Qwen3 VL 4B Thinking.