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Editorial · Models

Every model, measured.

Start with a research area, drill into a vendor, or page through the full index. Only models with at least one benchmark score appear — a model without a recorded score can’t be ranked.

Vendor:Areas overviewspeakleash · 253OpenAI · 85Google · 71Qwen · 52Alibaba · 47Anthropic · 44Microsoft · 35Meta · 30Mistral · 30DeepSeek · 28google · 19meta-llama · 19mistralai · 19Meta AI · 15CYFRAGOVPL · 14Zhipu AI · 13NVIDIA · 10SpeakLeash · 10internlm · 10xAI · 10ByteDance · 9Baidu · 8PLLuM · 8ibm-granite · 8microsoft · 8Amazon · 7Google DeepMind · 7MiniMax · 7Mistral AI · 7Remek · 7Shanghai AI Lab · 7allenai · 7utter-project · 7CohereForAI · 6Microsoft Research · 6Salesforce · 601-ai · 5Alibaba Cloud · 5Cohere · 5Moonshot AI · 5NousResearch · 5THUML · 5deepseek-ai · 5DeepMind · 4Facebook AI · 4IBM · 4Meituan · 4Stanford · 4THUDM · 4UC San Diego · 4VikParuchuri · 4gguf-iq · 4nvidia · 4openchat · 4tiiuae · 4Allen AI · 3BAAI · 3Du et al. · 3ForgeCode · 3Fudan University · 3IDEA Research · 3Liao et al. · 3Moonshot.AI · 3Nam Tuan Ly / NII · 3OPI-PG · 3OpenDataLab · 3ViCoS Lab Ljubljana · 3Xiaomi · 3Zhao et al. · 3gguf · 3gguf11bv30 · 3gguf7bv30 · 3upstage · 3+ 247 smaller vendors (291 models)
§ 01 · Medical models

50 models in Medical · page 1 of 1.

#ModelVendorParametersArchitectureSOTABenchmarksResults
001TorchXRayVisionCohen Lab—DenseNet-121 / ResNet266
002DenseNet-121 (Chest X-ray)Research8MDenseNet-121244
003MedNeXt-LGerman Cancer Research Center (DKFZ)62MConvNeXt-based encoder-decoder233
004CheXzeroHarvard/MIT—CLIP-based Vision-Language122
005ChebGAT-GCNAcademic—Chebyshev Spectral GCN + Graph Attention Network112
006MAACNNResearch—CNN122
007RAD-DINOMicrosoft—Self-supervised ViT122
008STU-Net-HZiyan Huang et al.1.4BScalable U-Net122
009CheXpert AUC MaximizerStanford—DenseNet-121 Ensemble111
010DeepASDResearch—Adversary-regularized GNN111
011SSAE + Softmax (Explainable ASD)Academic—Stacked Sparse Autoencoder + Softmax111
012SegMambaXing et al.53MMamba-based 3D segmentation111
013nnU-Net v2German Cancer Research Center (DKFZ)varies (~31M default)U-Net (self-configuring)—44
014STU-Net-LZiyan Huang et al.440MScalable U-Net—33
015ASD-SWNetResearch—Shared-weight CNN—12
016ASDFormerResearch—Transformer with Mixture of Experts—12
017BrainTWTAcademic—Temporal Random Walk + Transformer—12
018Causal fMRI ModelAcademic—Causality-inspired Deep Learning—12
019CheXNetStanford ML Group8MDenseNet-121—22
020GCNResearch—Graph Convolutional Network—12
021MVS-GCNResearch—Multi-view Site Graph Convolutional Network—12
022Random Forestscikit-learn—Random Forest—22
023SVM with Connectivity FeaturesResearch—Support Vector Machine—12
024Swin UNETRNVIDIA (MONAI)62MSwin Transformer encoder + U-Net decoder—22
025TransUNetChen et al. (JHU)105MViT encoder + U-Net decoder—22
026U-Mamba (Bot)Wang et al. (University of Toronto)59MMamba (SSM) + U-Net—22
027UNETRNVIDIA (MONAI)93MPure ViT encoder + U-Net decoder—22
028nnFormerZhou et al.150MInterleaved Transformer for volumetric segmentation—22
029AE-FCNResearch—Autoencoder + Fully Connected Network—11
030AL-NegatResearch—Graph Neural Network—11
031Abraham ConnectomesResearch—Connectome Analysis—11
032BioViLMicrosoft—Vision-Language Transformer—11
033BrainGNNResearch—Graph Neural Network—11
034BrainGTResearch—Graph Transformer—11
035ConVIRTNYU—Contrastive Vision-Language—11
036Deep Learning (Heinsfeld)Research—Deep Neural Network—11
037GLoRIAStanford—Vision-Language (Local + Global)—11
038LightM-UNetLiao et al.4MLightweight Mamba + U-Net—11
039MADE-for-ASDAcademic—Multi-Atlas Deep Ensemble Network—11
040MCBERTResearch—Multi-modal CNN-BERT—11
041MSalNETAcademic—Multi-site Adversarial Learning Network—11
042MedCLIPResearch—CLIP-based Vision-Language—11
043Multi-Atlas DNNResearch—Deep Neural Network—11
044Multi-Task TransformerResearch—Transformer—11
045PHGCL-DDGFormerResearch—Graph Transformer—11
046Plymouth DL ModelResearch—Deep Learning with XAI—11
047RGTNetAcademic—Residual Graph Transformer—11
048ResNet-50 (Chest X-ray)Research25MResNet-50—11
049SAM-Med3DUniversity Medical Center Hamburg-Eppendorf et al.387MSAM adapted for 3D volumes—11
050SegVolBAAI (Beijing Academy of AI)90MSAM-based volumetric segmentation—11