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Pixtral-12B vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
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Mistral AI
Pixtral 12B was introduced as Mistral's multimodal vision-language model, designed to understand and reason about both images and text. Built with 12 billion parameters for integrated visual and textual processing, it extends Mistral's capabilities into multimodal applications.
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Alibaba Cloud / Qwen Team
Qwen2.5-Omni 7B was created as a multimodal model supporting text, audio, and other modalities, designed to provide integrated understanding across diverse input types. Built with 7 billion parameters for efficient omni-modal processing, it extends AI capabilities beyond traditional text-only or vision-language boundaries.
6 months newer
Pixtral-12B
Mistral AI
2024-09-17
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
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Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
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Pixtral-12B
Average Score:66.2%
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Qwen2.5-Omni-7B
Average Score:66.3%(+0.0%)
Provider Availability & Performance
Available providers and their performance metrics
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Pixtral-12B
1 providers
Mistral AI
Throughput: 0.1 tok/s
Latency: 0.5ms
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Qwen2.5-Omni-7B
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Pixtral-12B
Avg Score:66.2%
Providers:1
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Qwen2.5-Omni-7B
Avg Score:66.3%(+0.0%)
Providers:0