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Llama 4 Behemoth vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
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Meta AI
Llama 4 Behemoth is a research-scale Mixture-of-Experts language model with approximately 2 trillion total parameters (288 billion active per inference), developed by Meta as a teacher model for the Llama 4 family. Available only in limited preview, it serves as the knowledge distillation source for Llama 4 Scout and Maverick. Behemoth targets research applications requiring the largest-scale open-weight model architecture from the Llama 4 generation.
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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.
Qwen2.5-Omni-7B
Alibaba / Qwen
2025-03-26
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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Llama 4 Behemoth
1 providers
Together AI
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Qwen2.5-Omni-7B
0 providers
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Llama 4 Behemoth
Avg Score:0.0%
Providers:1
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Qwen2.5-Omni-7B
Avg Score:0.0%
Providers:0