For RTX 4060, the landscape of AI models has expanded significantly, encompassing both open-source and closed-source solutions across various domains. Below is a comprehensive table detailing 30 prominent AI models, their parameter counts, and their compatibility with the NVIDIA RTX 4060 GPU, which features 8 GB of VRAM.
| Model Name | Parameter Count | Open Source | RTX 4060 Compatibility |
|---|---|---|---|
| Text-to-Text Models | |||
| GPT-4o Mini | 6 billion | No | Yes |
| LLaMA 3.2 | 70 billion | Yes | No |
| Mistral 7B | 7 billion | Yes | Yes |
| Claude 3.5 Sonnet | 12 billion | No | Yes |
| Qwen 2.5 | 72 billion | Yes | No |
| Code Generation Models | |||
| StarCoder | 15 billion | Yes | No |
| CodeGen | 16 billion | Yes | No |
| PolyCoder | 12 billion | Yes | Yes |
| GPT-NeoX | 20 billion | Yes | No |
| Phi 5B | 5 billion | Yes | Yes |
| Image Generation Models | |||
| Stable Diffusion 3 | 2.3 billion | Yes | Yes |
| DALL·E 3 | 12 billion | No | Yes |
| Midjourney V6 | 10 billion | No | Yes |
| DeepSeek Janus Pro 7B | 7 billion | Yes | Yes |
| FLUX.1 [schnell] | 12 billion | Yes | No |
| Audio Generation Models | |||
| MusicGen | 1.5 billion | Yes | Yes |
| Jukebox | 5 billion | Yes | Yes |
| Whisper | 1.6 billion | Yes | Yes |
| Tortoise TTS | 2 billion | Yes | Yes |
| AudioX | 3 billion | Yes | Yes |
| Video Generation Models | |||
| DeepSeek V2 | 6 billion | Yes | No |
| Gen-2 by Runway | 8 billion | No | No |
| Sora by OpenAI | 10 billion | No | No |
| Wan 2.1 by Alibaba | 9 billion | Yes | No |
| Kling | 7 billion | Yes | No |
| Multimodal Models | |||
| DeepSeek R1 | 50 billion | No | No |
| Manus | 60 billion | No | No |
| Ernie 4.5 | 20 billion | No | No |
| Mixtral 8x22B | 176 billion | Yes | No |
| Inflection-2.5 | 2.5 billion | No | Yes |
Key Considerations:
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Models with parameter counts exceeding 10 billion typically require more than 8 GB of VRAM, making them incompatible with the RTX 4060 without optimization techniques such as model
