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Phi 4 Mini Reasoning vs Pixtral Large
Comprehensive side-by-side LLM comparison
Pixtral Large leads with 35.9% higher average benchmark score. Pixtral Large supports multimodal inputs. Overall, Pixtral Large is the stronger choice for coding tasks.
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Microsoft
Phi 4 Mini Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 68.0% across 3 benchmarks. It excels particularly in MATH-500 (94.6%), AIME (57.5%), GPQA (52.0%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
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Mistral AI
Pixtral Large is a multimodal language model developed by Mistral AI. This model demonstrates exceptional performance with an average score of 80.5% across 7 benchmarks. It excels particularly in AI2D (93.8%), DocVQA (93.3%), ChartQA (88.1%). 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. Released in 2024, it represents Mistral AI's latest advancement in AI technology.
5 months newer
Pixtral Large
Mistral AI
2024-11-18
Phi 4 Mini Reasoning
Microsoft
2025-04-30
Performance Metrics
Context window and performance specifications
Average performance across 10 common benchmarks
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Phi 4 Mini Reasoning
Average Score:20.4%
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Pixtral Large
Average Score:56.4%(+35.9%)
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Knowledge Cutoff
Training data recency comparison
Phi 4 Mini Reasoning
2025-02-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Phi 4 Mini Reasoning
0 providers
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Pixtral Large
1 providers
Mistral AI
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Phi 4 Mini Reasoning
Avg Score:20.4%
Providers:0
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Pixtral Large
Avg Score:56.4%(+35.9%)
Providers:1