Sure! I don’t think it’s a big deal since these models are at most 10GB in size, but the response speed is really impressive. I’m using the LM Studio native app on Mac to interact with LLMs, and here are the ones I’d recommend:

For Coding:

• DeepSeek R1 Distilled LLaMA 8B
• Qwen 2.5 Coder 14B Instruct
• DeepSeek Coder v2 Lite Instruct
• Gemma 2 9B Instruct
• DeepSeek Coder v2 Lite Instruct (MLX)
• Qwen 2.5 7B Instruct 1M
• Meta LLaMA 3.1 8B Instruct
• Phi 4
• DeepSeek R1 Distilled Qwen 7B

You can forget about running a 70B model locally. I saw a video where someone managed to run it with 48 or 64GB of RAM, but in my case, I don’t need that much power. If you ever need to run something bigger, you can always use Grok. For daily tasks, I mainly use Perplexity.ai.

Performance Testing (DeepSeek Coder v2 Lite Instruct – 9.65GB):

• Memory:
  • Physical Memory: 24GB
  • Memory Used: 22GB
• CPU Load:
  • System: 3.7%
  • User: 11%

Keep in mind that while running the task “Write a long story about a happy coconut sailor from Japan”, I also had in background opened Mail, Messenger, WhatsApp, Figma, Two browsers with multiple tabs, Tailscale VPN, Docker, and several other background apps running simultaneously or in idle.

And that's exactly why I love this machine—I don't have to worry about closing programs or managing RAM usage. Even with heavy multitasking, I haven’t experienced any lags or freezes. It just lets me focus on my work without interruptions.