+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
DeepSeek VL2 Tiny vs Llama 4 Scout
Comprehensive side-by-side LLM comparison
DeepSeek VL2 Tiny leads with 3.5% higher average benchmark score. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
+
+
+
+
DeepSeek
DeepSeek VL2 Tiny is a multimodal language model developed by DeepSeek. It achieves strong performance with an average score of 63.1% across 14 benchmarks. It excels particularly in DocVQA (88.9%), ChartQA (81.0%), OCRBench (80.9%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2024, it represents DeepSeek's latest advancement in AI technology.
+
+
+
+
Meta
Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.
3 months newer
DeepSeek VL2 Tiny
DeepSeek
2024-12-13
Llama 4 Scout
Meta
2025-04-05
Performance Metrics
Context window and performance specifications
Average performance across 22 common benchmarks
+
+
+
+
DeepSeek VL2 Tiny
Average Score:40.2%(+3.5%)
+
+
+
+
Llama 4 Scout
Average Score:36.7%
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
DeepSeek VL2 Tiny
0 providers
+
+
+
+
Llama 4 Scout
6 providers
DeepInfra
+
+
+
+
DeepSeek VL2 Tiny
Avg Score:40.2%(+3.5%)
Providers:0
+
+
+
+
Llama 4 Scout
Avg Score:36.7%
Providers:6