sakd99/ai-models-database

1---2license: cc-by-4.03language:4- en5tags:6- ai7- llm8- large-language-models9- pricing10- api11- vram12- machine-learning13- benchmarks14pretty_name: Convly AI Models Database15size_categories:16- n<1K17configs:18- config_name: default19  data_files: convly-ai-models.csv20---21 22# Convly AI Models Database23 24A continuously updated, hand-verified dataset of **30+ AI language models** — specs, licenses, API pricing (USD per 1M tokens), and local-hardware (VRAM) requirements.25 26**Maintained by [Convly.ai](https://convly.ai/models/)** · Live interactive version: https://convly.ai/models/27 28## Fields29`name`, `slug`, `convly_url`, `developer`, `model_type`, `modality`, `parameters`, `context_window`, `max_output`, `license`, `open_weights`, `release_date`, `input_price` (USD/1M tokens), `output_price` (USD/1M tokens), `api_providers`, `vram_q4` (GB, 4-bit), `min_gpu`, `official_url`30 31## Coverage32Frontier + open-weight models as of July 2026: Claude (Opus 4.8, Fable 5, Sonnet 4.6, Haiku 4.5), GPT-5.5, Gemini 3.1 Pro / 3.5 Flash, DeepSeek V4-Pro / V4-Flash / R1, Qwen3 family, Llama 3.x / 4, Gemma 3, Mistral, Phi-4, GLM 5.2, Kimi K2.7 Code, NVIDIA Nemotron 3, and more.33 34## Why35Provider pricing pages are inconsistent and marketing-heavy. This dataset normalizes verified specs, **like-for-like per-million-token pricing**, and **practical 4-bit VRAM requirements** so you can tell instantly whether a model runs on your hardware and what it costs to call. It powers the [LLM VRAM Calculator](https://convly.ai/llm-vram-calculator/), the [AI API Cost Calculator](https://convly.ai/ai-api-cost-calculator/), and the [AI Price-Performance Index](https://convly.ai/ai-price-performance-index-2026/).36 37## Usage38```python39from datasets import load_dataset40ds = load_dataset("sakd99/ai-models-database")41print(ds["train"][0])42```43Or load the raw files directly:44```python45import pandas as pd46df = pd.read_csv("convly-ai-models.csv")47```48 49## License50**CC BY 4.0** — free to use, share and adapt with attribution to **[Convly.ai](https://convly.ai)** (a link to https://convly.ai/models/ is perfect).51 52## Citation53```54Convly.ai (2026). Convly AI Models Database [Data set]. https://convly.ai/models/55```56