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:

  • 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