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Llama 4 Scout vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Qwen2.5-Omni-7B leads with 37.9% higher average benchmark score. Llama 4 Scout is available on 6 providers. Overall, Qwen2.5-Omni-7B is the stronger choice for coding tasks.
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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.
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Alibaba Cloud / Qwen Team
Qwen2.5-Omni-7B is a multimodal language model developed by Alibaba Cloud / Qwen Team. The model shows competitive results across 45 benchmarks. It excels particularly in DocVQA (95.2%), VocalSound (93.9%), GSM8k (88.7%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
9 days newer
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
Llama 4 Scout
Meta
2025-04-05
Performance Metrics
Context window and performance specifications
Average performance across 49 common benchmarks
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Llama 4 Scout
Average Score:16.5%
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Qwen2.5-Omni-7B
Average Score:54.4%(+37.9%)
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:16.5%
Providers:6
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Qwen2.5-Omni-7B
Avg Score:54.4%(+37.9%)
Providers:0