Benchmark analysis of LFM2-24B-A2B by LiquidAI across 32 sourced tests on BenchLM.
According to BenchLM.ai, LFM2-24B-A2B ranks #102 out of 123 models with an overall score of 38/100. While not a frontier model, it offers specific advantages depending on the use case.
LFM2-24B-A2B is a proprietary model with a 32K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
Its strongest category is Mathematics (#92), while its weakest is Agentic (#109). This performance profile makes it particularly strong for mathematical reasoning, scientific computing, and quantitative analysis.
Creator
LiquidAI
Source Type
ProprietaryReasoning
Non-ReasoningContext Window
32K
Overall Score
Arena Elo
1062
LFM2-24B-A2B ranks #102 out of 123 models with an overall score of 38. It is created by LiquidAI and features a 32K context window.
LFM2-24B-A2B ranks #99 out of 123 models in knowledge and understanding benchmarks with an average score of 35.6. There are stronger options in this category.
LFM2-24B-A2B ranks #96 out of 123 models in coding and programming benchmarks with an average score of 18. There are stronger options in this category.
LFM2-24B-A2B ranks #92 out of 123 models in mathematics benchmarks with an average score of 50.4. There are stronger options in this category.
LFM2-24B-A2B ranks #99 out of 123 models in reasoning and logic benchmarks with an average score of 46.6. There are stronger options in this category.
LFM2-24B-A2B ranks #109 out of 123 models in agentic tool use and computer tasks benchmarks with an average score of 33.4. There are stronger options in this category.
LFM2-24B-A2B ranks #102 out of 123 models in multimodal and grounded tasks benchmarks with an average score of 41.7. There are stronger options in this category.
LFM2-24B-A2B ranks #100 out of 123 models in instruction following benchmarks with an average score of 68. There are stronger options in this category.
LFM2-24B-A2B ranks #95 out of 123 models in multilingual tasks benchmarks with an average score of 61.4. There are stronger options in this category.
LFM2-24B-A2B has a context window of 32K, which determines how much text it can process in a single interaction.
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