Datasets:
Download aggregates.csv from NoeFlandre/benchmark-llms-landuse-relevance: direct link, hf CLI and curl.
- Browser
- Download file 5.54 kB
-
https://huggingface.co/datasets/NoeFlandre/benchmark-llms-landuse-relevance/resolve/main/aggregates.csv
- Command line
-
hf download hf://datasets/NoeFlandre/benchmark-llms-landuse-relevance/aggregates.csv
-
curl -L -o aggregates.csv https://huggingface.co/datasets/NoeFlandre/benchmark-llms-landuse-relevance/resolve/main/aggregates.csv
5.54 kB
| model_id,language_count,n_items_total,accuracy_macro,balanced_accuracy_macro,f1_macro,precision_macro,recall_macro,matthews_corrcoef_macro,unparsed_rate_macro,f1_min,f1_max,f1_std | |
| Qwen/Qwen3.5-9B,85,25500,0.7851,0.7775,0.8151,0.7529,0.8919,0.5786,0.0,0.7358,0.883,0.0301 | |
| LiquidAI/LFM2.5-2.6B@sglang-throughput-b16,85,25500,0.7629,0.773,0.8106,0.7508,0.882,0.5636,0.0224,0.6748,0.8652,0.0412 | |
| LiquidAI/LFM2.5-2.6B+DSpark-throughput-b16,85,25500,0.7623,0.7744,0.8104,0.7547,0.8763,0.5644,0.0242,0.6916,0.8824,0.0423 | |
| LiquidAI/LFM2.5-2.6B,85,25500,0.7602,0.7536,0.8029,0.7253,0.9001,0.5352,0.0042,0.7017,0.8546,0.0379 | |
| Qwen/Qwen3-4B-Instruct-2507,85,25500,0.7622,0.755,0.7905,0.7356,0.864,0.5344,0.0,0.4153,0.8571,0.0761 | |
| Qwen/Qwen3-4B,85,25500,0.7472,0.745,0.7634,0.7564,0.7784,0.4965,0.0,0.3192,0.8406,0.07 | |
| google/gemma-4-E4B-it,85,25500,0.7728,0.78,0.7509,0.873,0.6719,0.5726,0.0,0.4796,0.8671,0.0968 | |
| Qwen/Qwen3-8B,85,25500,0.7553,0.7606,0.7442,0.831,0.6818,0.5283,0.0,0.496,0.8537,0.0663 | |
| Qwen/Qwen3.5-0.8B,85,25500,0.6116,0.5882,0.7217,0.5883,0.939,0.2393,0.0,0.6805,0.7717,0.0244 | |
| LiquidAI/LFM2.5-8B-A1B,85,25500,0.7047,0.7056,0.7179,0.7318,0.7096,0.4128,0.0016,0.5057,0.8349,0.0821 | |
| LiquidAI/LFM2.5-8B-A1B+DSpark-throughput-b16,85,25500,0.6995,0.7047,0.6992,0.7559,0.655,0.4118,0.0029,0.4591,0.8439,0.0813 | |
| LiquidAI/LFM2.5-2.6B@logprob,85,25500,0.5353,0.5022,0.6965,0.5344,0.9998,0.0191,0.0,0.6943,0.7162,0.0028 | |
| LiquidAI/LFM2.5-Encoder-350M,15,4500,0.534,0.5007,0.696,0.5337,1.0,0.01,0.0,0.6957,0.6987,0.0008 | |
| LiquidAI/LFM2.5-350M,85,25500,0.5333,0.5,0.6957,0.5333,1.0,0.0,0.0,0.6957,0.6957,0.0 | |
| Qwen/Qwen3-0.6B,85,25500,0.5333,0.5,0.6957,0.5333,1.0,0.0,0.0,0.6957,0.6957,0.0 | |
| MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7,85,25500,0.5332,0.5001,0.6951,0.5334,0.9975,0.0007,0.0,0.69,0.6972,0.0017 | |
| BalaRajesh1/mmbert-small-nli,85,25500,0.5327,0.4994,0.695,0.533,0.9985,-0.0105,0.0,0.69,0.6972,0.0013 | |
| fastino/gliner2.5-multi-v1,85,25500,0.5408,0.5094,0.6949,0.5382,0.981,0.0639,0.0,0.6281,0.708,0.01 | |
| LiquidAI/LFM2.5-8B-A1B@sglang-throughput-b16,85,25500,0.6936,0.6999,0.6915,0.753,0.644,0.4024,0.0041,0.4549,0.8224,0.0834 | |
| convaiinnovations/laya-multilingual,85,25500,0.5351,0.5049,0.6866,0.5356,0.9576,0.0354,0.0,0.5829,0.7198,0.0255 | |
| Alibaba-NLP/gte-multilingual-reranker-base,85,25500,0.5412,0.5201,0.6571,0.5456,0.8361,0.0593,0.0,0.5016,0.7078,0.0429 | |
| Qwen/Qwen3.5-4B,85,25500,0.6833,0.6999,0.5936,0.9093,0.4515,0.4522,0.0,0.3196,0.7875,0.1123 | |
| mistralai/Ministral-3-8B-Instruct-2512-BF16,85,25500,0.6688,0.6869,0.5625,0.9164,0.4156,0.4344,0.0,0.1047,0.7905,0.119 | |
| google/gemma-4-E2B-it,85,25500,0.6389,0.6577,0.5209,0.8746,0.3768,0.3732,0.0,0.2581,0.6667,0.0899 | |
| LiquidAI/LFM2.5-1.2B-Instruct,85,25500,0.6038,0.6158,0.516,0.7101,0.4351,0.2492,0.0,0.2094,0.7451,0.1591 | |
| LiquidAI/LFM2.5-1.2B-Instruct+DSpark-throughput-b16,85,25500,0.6024,0.6148,0.5095,0.7118,0.4274,0.2482,0.0,0.202,0.7427,0.1641 | |
| LiquidAI/LFM2.5-1.2B-Instruct@sglang-throughput-b16,85,25500,0.6024,0.6148,0.5095,0.7118,0.4274,0.2482,0.0,0.202,0.7427,0.1641 | |
| LiquidAI/LFM2.5-VL-3B,85,25500,0.6061,0.6239,0.4896,0.7951,0.3571,0.2912,0.0,0.3251,0.5726,0.0548 | |
| LiquidAI/LFM2.5-VL-3B+DSpark-throughput-b16,85,25500,0.6059,0.6237,0.4889,0.7951,0.3564,0.2909,0.0,0.3251,0.5783,0.0555 | |
| LiquidAI/LFM2.5-VL-3B@sglang-throughput-b16,85,25500,0.6059,0.6237,0.4889,0.7951,0.3564,0.2909,0.0,0.3251,0.5783,0.0555 | |
| microsoft/Phi-4-mini-instruct,85,25500,0.6026,0.6221,0.4598,0.8295,0.3297,0.3005,0.0,0.172,0.6717,0.1016 | |
| HuggingFaceTB/SmolLM3-3B,85,25500,0.6071,0.6277,0.4551,0.8619,0.3187,0.3207,0.0,0.1053,0.6275,0.1104 | |
| tiiuae/Falcon3-3B-Instruct,85,25500,0.5909,0.6099,0.4432,0.7935,0.3261,0.2673,0.0,0.0936,0.6725,0.136 | |
| ibm-granite/granite-3.3-2b-instruct,85,25500,0.5657,0.5846,0.4061,0.7213,0.3013,0.2016,0.0,0.0814,0.725,0.1456 | |
| unsloth/Qwen3.8-27B-GGUF@UD-IQ2_XXS,85,25500,0.5863,0.6113,0.3664,0.9521,0.2363,0.321,0.0,0.0606,0.7209,0.1383 | |
| allenai/Olmo-3-7B-Instruct,85,25500,0.5688,0.5929,0.3469,0.8565,0.2315,0.2582,0.0,0.0244,0.6468,0.1542 | |
| Qwen/Qwen3.5-2B,85,25500,0.5613,0.5864,0.3306,0.8739,0.209,0.2569,0.0,0.1059,0.5339,0.0924 | |
| mistralai/Ministral-3-3B-Instruct-2512-BF16,85,25500,0.5561,0.5815,0.3173,0.8811,0.201,0.2507,0.0,0.0833,0.6258,0.0919 | |
| utter-project/EuroLLM-9B-Instruct-2512,85,25500,0.5276,0.5564,0.2125,0.9213,0.124,0.2129,0.0,0.0,0.5494,0.098 | |
| tiiuae/Falcon3-7B-Instruct,85,25500,0.5139,0.5438,0.1657,0.9132,0.095,0.1806,0.0,0.0,0.4293,0.1055 | |
| MoritzLaurer/bge-m3-zeroshot-v2.0,85,25500,0.4959,0.5247,0.1627,0.6953,0.0934,0.0927,0.0,0.0,0.29,0.0577 | |
| knowledgator/gliclass-multilang-mini,85,25500,0.4843,0.5121,0.1599,0.6036,0.0946,0.0425,0.0,0.0238,0.4118,0.065 | |
| ibm-granite/granite-4.1-3b,85,25500,0.5111,0.5415,0.1547,0.9729,0.0863,0.1864,0.0,0.0124,0.3981,0.0817 | |
| allenai/OLMo-2-1124-7B-Instruct,85,25500,0.5035,0.5341,0.1324,0.929,0.0754,0.1543,0.0,0.0,0.4381,0.1051 | |
| Qwen/Qwen3-1.7B,85,25500,0.4893,0.5209,0.0843,0.7628,0.0468,0.1093,0.0,0.0,0.3518,0.0866 | |
| tiiuae/Falcon-H1-3B-Instruct,85,25500,0.4878,0.5202,0.08,0.865,0.0428,0.1179,0.0009,0.0,0.2235,0.06 | |
| swiss-ai/Apertus-8B-Instruct-2509,85,25500,0.4761,0.5089,0.0346,0.8809,0.0178,0.0813,0.0,0.0,0.1503,0.0276 | |
| Qwen/Qwen3-Reranker-4B,85,25500,0.474,0.5066,0.0337,0.6448,0.0175,0.0501,0.0,0.0,0.1272,0.031 | |
| tiiuae/Falcon3-1B-Instruct,85,25500,0.4705,0.5035,0.0191,0.418,0.0099,0.0263,0.0002,0.0,0.1059,0.0284 | |
| Qwen/Qwen3-Reranker-0.6B,85,25500,0.4673,0.5006,0.0022,0.1529,0.0011,0.0088,0.0,0.0,0.0247,0.0054 | |
| mixedbread-ai/mxbai-rerank-base-v2,85,25500,0.4669,0.5002,0.0013,0.029,0.0007,0.0012,0.0,0.0,0.0599,0.0076 | |