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Gemini 2.5 Flash-Lite vs Magistral Small 2506
Comprehensive side-by-side LLM comparison
Gemini 2.5 Flash-Lite leads with 19.8% higher average benchmark score. Gemini 2.5 Flash-Lite supports multimodal inputs. Overall, Gemini 2.5 Flash-Lite is the stronger choice for coding tasks.
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Gemini 2.5 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in FACTS Grounding (84.1%), Global-MMLU-Lite (81.1%), MMMU (72.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 2025, it represents Google's latest advancement in AI technology.
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Mistral AI
Magistral Small 2506 is a language model developed by Mistral AI. It achieves strong performance with an average score of 63.2% across 4 benchmarks. Notable strengths include AIME 2024 (70.7%), GPQA (68.2%), AIME 2025 (62.8%). 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.
7 days newer
Magistral Small 2506
Mistral AI
2025-06-10
Gemini 2.5 Flash-Lite
2025-06-17
Performance Metrics
Context window and performance specifications
Average performance across 14 common benchmarks
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Gemini 2.5 Flash-Lite
Average Score:37.9%(+19.8%)
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Magistral Small 2506
Average Score:18.1%
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Knowledge Cutoff
Training data recency comparison
Gemini 2.5 Flash-Lite
2025-01-01
Magistral Small 2506
2025-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.5 Flash-Lite
1 providers
Throughput: 5.69 tok/s
Latency: 0.44ms
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Magistral Small 2506
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Gemini 2.5 Flash-Lite
Avg Score:37.9%(+19.8%)
Providers:1
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Magistral Small 2506
Avg Score:18.1%
Providers:0