Codesota · Models1,357 models indexed · 15 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 · Meta AI models
15 models from Meta AI · page 1 of 1.
| # | Model | Vendor | Parameters | Architecture | SOTA | Benchmarks | Results |
|---|---|---|---|---|---|---|---|
| 001 | GENRE | Meta AI | — | Autoregressive seq2seq entity retrieval (BART) | 1 | 1 | 1 |
| 002 | SeamlessM4T v2 Large | Meta AI | 2.3B | Unified multilingual/multimodal transformer (UnitY2) | 1 | 1 | 1 |
| 003 | wav2vec 2.0 Large (960h) | Meta AI | 317M | CNN feature encoder + Transformer | 9 | 12 | |
| 004 | Llama-2-70B-chat | Meta AI | — | Llama 2 70B with RLHF chat fine-tuning | 1 | 3 | |
| 005 | HuBERT Large (LS-960) | Meta AI | 317M | CNN + Transformer (BERT-style) | 1 | 2 | |
| 006 | ViTDet-H (MAE) | Meta AI | Unknown | Plain ViT-H backbone with simple feature pyramid, Cascade Mask RCNN head | 1 | 2 | |
| 007 | Voicebox | Meta AI | 330M | Flow matching (non-autoregressive) | 2 | 2 | |
| 008 | DINOv2 (ViT-g) + Linear | Meta AI | Unknown | Self-supervised ViT-giant + linear head | 1 | 1 | |
| 009 | Fairseq S2T (MuST-C) | Meta AI | ~150M | Conformer encoder + transformer decoder | 1 | 1 | |
| 010 | Mask2Former (Swin-L) | Meta AI | Unknown | Masked-attention Mask Transformer + Swin-L | 1 | 1 | |
| 011 | Mask2Former (Swin-L) LVIS | Meta AI | Unknown | Masked-attention Mask Transformer + Swin-L | 1 | 1 | |
| 012 | MusicGen Large | Meta AI | 3.3B | Single-stage transformer LM over EnCodec tokens | 1 | 1 | |
| 013 | NLLB-3.3B | Meta AI | 3.3B | Transformer (dense MT) | 1 | 1 | |
| 014 | ViTDet-H | Meta AI | Unknown | Plain ViT-Huge + Cascade Mask R-CNN | 1 | 1 | |
| 015 | convnext_base.fb_in22k_ft_in1k | Meta AI | — | ConvNeXt-B, IN22K pre-train, IN1K fine-tune | 1 | 1 |