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Mistral Small 3.1 24B Base vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
Qwen2.5-Omni-7B leads with 50.0% higher average benchmark score. Overall, Qwen2.5-Omni-7B is the stronger choice for coding tasks.
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Mistral AI
Mistral Small 3.1 24B Base is a multimodal language model developed by Mistral AI. It achieves strong performance with an average score of 62.9% across 5 benchmarks. It excels particularly in MMLU (81.0%), TriviaQA (80.5%), MMMU (59.3%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. 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 Mistral AI'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.
10 days newer
Mistral Small 3.1 24B Base
Mistral AI
2025-03-17
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
Performance Metrics
Context window and performance specifications
Average performance across 47 common benchmarks
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Mistral Small 3.1 24B Base
Average Score:6.7%
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Qwen2.5-Omni-7B
Average Score:56.7%(+50.0%)
Provider Availability & Performance
Available providers and their performance metrics
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Mistral Small 3.1 24B Base
1 providers
Mistral AI
Throughput: 137.1 tok/s
Latency: 0.23ms
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Qwen2.5-Omni-7B
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Mistral Small 3.1 24B Base
Avg Score:6.7%
Providers:1
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Qwen2.5-Omni-7B
Avg Score:56.7%(+50.0%)
Providers:0