Codesota · Models1,357 models indexed · 71 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 · Google models
71 models from Google · page 2 of 2.
| # | Model | Vendor | Parameters | Architecture | SOTA | Benchmarks | Results |
|---|---|---|---|---|---|---|---|
| 051 | EfficientNetV2-L | 120M | CNN | 1 | 1 | ||
| 052 | Gemini 2.0 Flash Thinking | — | — | 1 | 1 | ||
| 053 | Gemini 2.5 Flash-Lite | — | — | 1 | 1 | ||
| 054 | Gemini 2.5 Pro Preview | — | — | 1 | 1 | ||
| 055 | Gemini 3.1 Flash-Lite | — | — | 1 | 1 | ||
| 056 | Gemini Diffusion | — | — | 1 | 1 | ||
| 057 | Gemini Flash 2 | — | Multimodal LLM | 1 | 1 | ||
| 058 | Gemma 3 | — | — | 1 | 1 | ||
| 059 | GoogLeNet | — | — | 1 | 1 | ||
| 060 | Google Translate | — | Transformer (NMT) | 1 | 1 | ||
| 061 | MusicLM | ~1.5B | Hierarchical autoregressive (SoundStream+w2v-BERT+MuLan) | 1 | 1 | ||
| 062 | PaLM 2 (Large) | Unknown | Transformer (decoder-only) | 1 | 1 | ||
| 063 | PaLM 540B (CoT) | — | — | 1 | 1 | ||
| 064 | PaLM 540B (Self-Consistency) | — | — | 1 | 1 | ||
| 065 | SoViT-400M/14 | 400M | Compute-optimal ViT shape | 1 | 1 | ||
| 066 | TAPAS-large | 340M | BERT-large (table-augmented) | 1 | 1 | ||
| 067 | ViT-22B/14 | 22B | Scaled Vision Transformer 22B | 1 | 1 | ||
| 068 | ViT-G/14 | 1.8B | Vision Transformer | 1 | 1 | ||
| 069 | ViT-L/16 | 307M | Vision Transformer | 1 | 1 | ||
| 070 | coatnet_2_rw_224.sw_in12k_ft_in1k | — | CoAtNet-2 RW, IN12K -> IN1K fine-tune | 1 | 1 | ||
| 071 | maxvit_base_tf_512.in1k | — | MaxViT base, 512 input, timm | 1 | 1 |