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Llama 4 Scout vs QvQ-72B-Preview
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
QVQ-72B Preview was introduced as an experimental visual question answering model, designed to combine vision and language understanding for complex reasoning tasks. Built to demonstrate advanced multimodal reasoning capabilities, it represents Qwen's exploration into models that can analyze and reason about visual information.
3 months newer
QvQ-72B-Preview
Alibaba Cloud / Qwen Team
2024-12-25
Llama 4 Scout
Meta
2025-04-05
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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Llama 4 Scout
Average Score:70.0%
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QvQ-72B-Preview
Average Score:70.8%(+0.8%)
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:70.0%
Providers:6
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QvQ-72B-Preview
Avg Score:70.8%(+0.8%)
Providers:0