OpenAI#
AI research company known for GPT models, ChatGPT, and DALL-E
Organization Information#
| Field | Value |
|---|---|
| Author ID | openai |
| Type | 🚀 AI Startups |
| Website | https://openai.com |
| Total Models | 79 |
| Available On | 4 providers |
Models#
DALL-E#
| Model | Providers | Context | Capabilities |
|---|---|---|---|
| dall-e-2 | openai | N/A | Text |
| dall-e-3 | openai | N/A | Text |
GPT#
Embeddings#
| Model | Providers | Context | Capabilities |
|---|---|---|---|
| text-embedding-3-large | openai | N/A | Text |
| text-embedding-3-small | openai | N/A | Text |
| text-embedding-ada-002 | openai | N/A | Text |
Whisper#
| Model | Providers | Context | Capabilities |
|---|---|---|---|
| Whisper Large | google-vertex | N/A | Text |
| whisper-1 | openai | N/A | Text |
| whisper-large-v3 | groq | 448 | Text |
| whisper-large-v3-turbo | groq | 448 | Text |
Other#
| Model | Providers | Context | Capabilities |
|---|---|---|---|
| Clip Vit Base Patch32 | google-vertex | N/A | Text |
| Openclip | google-vertex | N/A | Text |
| babbage-002 | openai | N/A | Text |
| compound-beta | groq | 131.1k | Text |
| compound-beta-mini | groq | 131.1k | Text |
| davinci-002 | openai | N/A | Text |
| groq/compound | groq | 131.1k | Text |
| groq/compound-mini | groq | 131.1k | Text |
| o1 | openai | 200k | Text |
| o1-2024-12-17 | openai | N/A | Text |
| o1-mini | openai | 128k | Text |
| o1-mini-2024-09-12 | openai | N/A | Text |
| o3 | openai | 200k | Text |
| o3-2025-04-16 | openai | N/A | Text |
| o3-mini | openai | 200k | Text |
| o3-mini-2025-01-31 | openai | N/A | Text |
| o4-mini | openai | 200k | Text |
| o4-mini-2025-04-16 | openai | N/A | Text |
| omni-moderation-2024-09-26 | openai | N/A | Text |
| omni-moderation-latest | openai | N/A | Text |
| tts-1 | openai | N/A | Text |
| tts-1-1106 | openai | N/A | Text |
| tts-1-hd | openai | N/A | Text |
| tts-1-hd-1106 | openai | N/A | Text |
Provider Availability#
Models from this author are available through the following providers:
- openai - 65 models
- groq - 8 models
- google-vertex - 5 models
- cerebras - 1 model
Research & Development#
Key research areas include:
- Reinforcement Learning from Human Feedback (RLHF) - Pioneering work in aligning models with human preferences
- Scaling Laws - Research on how model performance scales with compute and data
- Multimodal Learning - Combining text, vision, and audio in unified models
- AI Safety - Work on alignment, robustness, and beneficial AI
See Also#
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