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Llama 4 Scout vs Qwen2-VL-72B-Instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Llama 4 Scout is available on 6 providers. Both models have their strengths depending on your specific coding needs.
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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.
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Alibaba Cloud / Qwen Team
Qwen2-VL 72B was developed as a large vision-language model, designed to handle multimodal tasks combining visual and textual understanding. Built with 72 billion parameters for integrated vision and language processing, it enables applications requiring sophisticated analysis of images alongside text.
7 months newer
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
2024-08-29
Llama 4 Scout
Meta
2025-04-05
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Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Llama 4 Scout
Average Score:88.8%(+0.5%)
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Qwen2-VL-72B-Instruct
Average Score:88.3%
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Knowledge Cutoff
Training data recency comparison
Qwen2-VL-72B-Instruct
2023-06-30
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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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
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Llama 4 Scout
Avg Score:88.8%(+0.5%)
Providers:6
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Qwen2-VL-72B-Instruct
Avg Score:88.3%
Providers:0