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Llama 4 Maverick vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Llama 4 Maverick leads with 4.4% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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Meta AI
Llama 4 Maverick, released by Meta on April 5, 2025, is a natively multimodal Mixture-of-Experts large language model with 400 billion total parameters and 17 billion active parameters per inference. It features a 1M token context window and supports text and image input, enabling strong performance on both language and vision tasks. Maverick targets open-source deployments requiring large-scale multimodal reasoning, released under Meta's custom license.
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Alibaba / Qwen
Qwen2.5-Omni-7B is a 7-billion-parameter end-to-end multimodal model from Alibaba, released in March 2025 as part of the Omni series designed to unify perception and generation across text, images, audio, and video in a single model architecture. Unlike pipeline-based multimodal systems, it processes all modalities end-to-end and can generate both text and speech outputs, targeting use cases in voice assistants, multimodal agents, and real-time interactive applications. Its compact size made it notable for on-device and resource-constrained multimodal deployments.
10 days newer
Qwen2.5-Omni-7B
Alibaba / Qwen
2025-03-26
Llama 4 Maverick
Meta AI
2025-04-05
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Llama 4 Maverick
Average Score:77.6%(+4.4%)
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Qwen2.5-Omni-7B
Average Score:73.2%
Performance comparison across key benchmark categories
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Llama 4 Maverick
Coding77.6%(+4.4%)
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Qwen2.5-Omni-7B
Coding73.2%
Provider Availability & Performance
Available providers and their performance metrics
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Llama 4 Maverick
1 providers
Together AI
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Qwen2.5-Omni-7B
0 providers
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Llama 4 Maverick
Avg Score:77.6%(+4.4%)
Providers:1
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Qwen2.5-Omni-7B
Avg Score:73.2%
Providers:0