---
license: cc-by-4.0
language:
- en
tags:
- ai
- llm
- large-language-models
- pricing
- api
- vram
- machine-learning
- benchmarks
pretty_name: Convly AI Models Database
size_categories:
- n<1K
configs:
- config_name: default
  data_files: convly-ai-models.csv
---

# Convly AI Models Database

A continuously updated, hand-verified dataset of **30+ AI language models** — specs, licenses, API pricing (USD per 1M tokens), and local-hardware (VRAM) requirements.

**Maintained by [Convly.ai](https://convly.ai/models/)** · Live interactive version: https://convly.ai/models/

## Fields
`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`

## Coverage
Frontier + 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.

## Why
Provider 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/).

## Usage
```python
from datasets import load_dataset
ds = load_dataset("sakd99/ai-models-database")
print(ds["train"][0])
```
Or load the raw files directly:
```python
import pandas as pd
df = pd.read_csv("convly-ai-models.csv")
```

## License
**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).

## Citation
```
Convly.ai (2026). Convly AI Models Database [Data set]. https://convly.ai/models/
```