+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Llama 4 Scout vs Qwen2.5 VL 32B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 VL 32B Instruct leads with 4.5% higher average benchmark score. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
+
+
+
+
Meta
Llama 4 Scout was created as an exploratory variant in the Llama 4 family, designed to investigate new architectures and optimization strategies. Built as part of Meta's commitment to advancing open-source AI, it serves as a testbed for innovations that may inform future model releases.
+
+
+
+
Alibaba Cloud / Qwen Team
Qwen2.5-VL 32B was developed as a mid-sized vision-language model, designed to balance multimodal capability with practical deployment considerations. Built with 32 billion parameters for vision and language integration, it serves applications requiring strong visual understanding without flagship-scale resources.
1 month newer
Qwen2.5 VL 32B Instruct
Alibaba Cloud / Qwen Team
2025-02-28
Llama 4 Scout
Meta
2025-04-05
+
+
+
+
+
+
+
+
+
+
+
+
Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
+
+
+
+
Llama 4 Scout
Average Score:70.4%
+
+
+
+
Qwen2.5 VL 32B Instruct
Average Score:74.9%(+4.5%)
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
Llama 4 Scout
6 providers
DeepInfra
Throughput: 76.1 tok/s
Latency: 0.31ms
Fireworks
Throughput: 116.1 tok/s
Latency: 0.53ms
Groq
Throughput: 776.1 tok/s
Latency: 1.08ms
Lambda
Throughput: 139.7 tok/s
Latency: 0.43ms
Novita
+
+
+
+
Llama 4 Scout
Avg Score:70.4%
Providers:6
+
+
+
+
Qwen2.5 VL 32B Instruct
Avg Score:74.9%(+4.5%)
Providers:0