Codesota · Models1,357 models indexed · 896 match filter
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 · Computer Vision models
896 models in Computer Vision · page 12 of 18.
| # | Model | Vendor | Parameters | Architecture | SOTA | Benchmarks | Results |
|---|---|---|---|---|---|---|---|
| 551 | Azure OCR | Microsoft | — | Cloud OCR Service | 1 | 1 | |
| 552 | BERT [BERT] | Unknown | Unknown | Unknown | 1 | 1 | |
| 553 | BEiT | — | — | — | 1 | 1 | |
| 554 | BEiT-3 (ViT-L) | Microsoft | Unknown | Multiway Transformer (ViT-L/14) | 1 | 1 | |
| 555 | BM25-HierSumm (query: step + method + article titles) | Unknown | Unknown | Unknown | 1 | 1 | |
| 556 | BM25-HierSumm (query: step + method titles) | Unknown | Unknown | Unknown | 1 | 1 | |
| 557 | BM25-HierSumm (query: step title) | Unknown | Unknown | Unknown | 1 | 1 | |
| 558 | Binder | Unknown | Unknown | Unknown | 1 | 1 | |
| 559 | BioGPT-Large | — | — | — | 1 | 1 | |
| 560 | CCD-ViT-Tiny | Unknown | Unknown | Unknown | 1 | 1 | |
| 561 | CDeC-Net | Unknown | Unknown | Unknown | 1 | 1 | |
| 562 | CDistNet | Research | Unknown | Content & Spatial Distribution Network for scene text recognition | 1 | 1 | |
| 563 | CES (query: method + article + steps titles) | Unknown | Unknown | Unknown | 1 | 1 | |
| 564 | CES (query: method + article titles) | Unknown | Unknown | Unknown | 1 | 1 | |
| 565 | CES (query: method title) | Unknown | Unknown | Unknown | 1 | 1 | |
| 566 | CES (query: step + method + article titles) | Unknown | Unknown | Unknown | 1 | 1 | |
| 567 | CES (query: step + method titles) | Unknown | Unknown | Unknown | 1 | 1 | |
| 568 | CES (query: step title) | Unknown | Unknown | Unknown | 1 | 1 | |
| 569 | CLIP | — | — | — | 1 | 1 | |
| 570 | CLIP4STR | Research | Unknown | CLIP-based Scene Text Recognition | 1 | 1 | |
| 571 | CLIP4STR-B (DataComp-1B) | Unknown | Unknown | Unknown | 1 | 1 | |
| 572 | CLIP4STR-H (DFN-5B) | Zhao et al. | Unknown | CLIP ViT-H/14 visual branch + cross-modal branch, pre-trained on DFN-5B | 1 | 1 | |
| 573 | CLIP4STR-L (RBU 6.5M) | Zhao et al. | Unknown | CLIP ViT-L/14 visual branch + cross-modal branch, trained on RBU 6.5M real data | 1 | 1 | |
| 574 | CUTeOCR | CUHK / HIT | Unknown | Scene text detector | 1 | 1 | |
| 575 | CW_Detection | Independent | — | — | 1 | 1 | |
| 576 | Chain-of-Table | Unknown | Unknown | Unknown | 1 | 1 | |
| 577 | Chandra | — | — | — | 1 | 1 | |
| 578 | Chandra 2 | — | — | — | 1 | 1 | |
| 579 | Co-DETR (Swin-L) | — | — | — | 1 | 1 | |
| 580 | Co-DINO (ViT-L) | Sensetime / Sense-X | ~600M | DINO transformer detector with ViT-L backbone and collaborative hybrid assignment training | 1 | 1 | |
| 581 | Co-DINO-Deformable-DETR++ (Swin-L, 36 epochs) | — | — | — | 1 | 1 | |
| 582 | CoTexT | Case Western Reserve University | — | Transformer encoder-decoder | 1 | 1 | |
| 583 | CodeBERT+AdvFusion | University of Leicester | 125M | transformer | 1 | 1 | |
| 584 | CodeT5+ 2B | Salesforce | Unknown | T5-based encoder-decoder | 1 | 1 | |
| 585 | CodeTrans-MT-Large | Unknown | Unknown | Unknown | 1 | 1 | |
| 586 | ConvNeXt V2 Base | Meta | 89M | CNN | 1 | 1 | |
| 587 | ConvNeXt V2 Tiny | Meta | 28M | CNN | 1 | 1 | |
| 588 | ConvStem | Unknown | Unknown | Unknown | 1 | 1 | |
| 589 | Cross-Modal | Unknown | Unknown | Unknown | 1 | 1 | |
| 590 | D-FINE-L | — | — | — | 1 | 1 | |
| 591 | D-FINE-X | Peterande et al. | Unknown | DETR + Fine-grained Distribution Refinement (FDR) | 1 | 1 | |
| 592 | DB-ResNet-50 (800) | Unknown | Unknown | Unknown | 1 | 1 | |
| 593 | DB-ResNet50 (1024) | Unknown | Unknown | Unknown | 1 | 1 | |
| 594 | DBNet | AAAI 2020 | — | — | 1 | 1 | |
| 595 | DBNet++ | TPAMI 2022 | — | — | 1 | 1 | |
| 596 | DEIM-D-FINE-X | — | — | — | 1 | 1 | |
| 597 | DEIMv2-L | — | — | — | 1 | 1 | |
| 598 | DEIMv2-M | — | — | — | 1 | 1 | |
| 599 | DEIMv2-S | — | — | — | 1 | 1 | |
| 600 | DEIMv2-X | — | — | — | 1 | 1 |