Head-to-Head Comparison: The 5 Most Noteworthy Locally Runnable LLMs
After reviewing each of these five models individually, it’s helpful to see them side-by-side. Below is a comprehensive comparison covering size, architecture, best quantization, typical VRAM/RAM requirements, and key capabilities.
Comparison Table
| Model | Size | Architecture | Best Quant. | VRAM/RAM | Coding | Reasoning | Speed | Best Use | Overall |
|---|---|---|---|---|---|---|---|---|---|
| Llama 3.3 70B | 70B | Dense | 4-bit | 38-42GB | 8.5 | 9 | 7 | Max intelligence | 8 |
| Qwen 2.5 72B | 72B | Dense | 4-bit | 40-44GB | 9.5 | 9 | 7 | Coding & multilingual | 8.5 |
| Gemma 3 12B | 12B | Dense | 4-bit | 8-10GB | 7.5 | 8 | 8.5 | General AI | 9 |
| Phi-4 | ~14B | Dense | 4-bit | 9-11GB | 7.5 | 9 | 9 | Reasoning, CPU | 9.5 |
| Mistral Nemo 12B | 12B | Dense | 4-bit | 8-10GB | 8 | 8.5 | 9 | Agentic/tool-use | 9 |
Head-to-Head Questions Answered
- Which is the best overall local LLM?
Mistral Nemo 12B and Gemma 3 12B tie for the best overall balance for most users, but Phi-4 edges them out slightly due to its exceptional reasoning capabilities and CPU-friendly efficiency. - Which is the most intelligent?
Llama 3.3 70B Instruct and Qwen 2.5 72B Instruct are tied for raw intelligence, with Qwen 2.5 having a slight edge in coding and multilingual tasks. - Which is the best for coding?
Qwen 2.5 72B Instruct is unequivocally the best for coding among locally runnable models, rivaling or exceeding GPT-4 in many programming tasks. - Which gives the best performance for limited VRAM?
Gemma 3 12B and Mistral Nemo 12B both require only 8-10GB VRAM at 4-bit quantization, but Gemma 3 12B has slightly better Google-trained reasoning. - Which is the best choice for a 12 GB GPU?
Phi-4 or Mistral Nemo 12B are the best choices for a 12GB GPU, with Phi-4 excelling in reasoning and Mistral Nemo excelling in tool-use. - Which is the best choice for a 24 GB GPU?
A 24GB GPU can run Gemma 3 12B, Phi-4, or Mistral Nemo 12B comfortably at higher quantizations (6-bit or 8-bit), but cannot fit the 70B+ models without severe degradation. - Which is the best choice for Apple Silicon?
Phi-4 and Gemma 3 12B are excellent on Apple Silicon Macs with 16GB+ unified memory, offering fast inference and minimal power consumption. - Which is the best CPU-only model?
Phi-4 is the best choice for CPU-only systems due to its exceptional efficiency and reasoning capabilities, generating 5-8 tokens/sec on 16GB RAM. - Which model offers the best balance between intelligence, speed and hardware requirements?
Mistral Nemo 12B offers the best overall balance, with strong general intelligence, excellent speed, agentic/tool-use optimization, and only 8-10GB VRAM requirements. - Which model would you personally choose for a high-end local AI workstation, and why?
For a high-end local AI workstation with 48GB+ VRAM or unified memory, I would choose Qwen 2.5 72B Instruct due to its unmatched coding capabilities, superior multilingual support, and exceptional mathematical reasoning.
The Local LLM I Would Actually Run
If I had to choose one model to run locally on a typical consumer or prosumer workstation today, it would be Phi-4. Here’s why:
- Hardware accessibility: At 9-11GB VRAM for 4-bit quantization, Phi-4 runs comfortably on any modern 12GB GPU (RTX 3060 12GB, RTX 4070) or Apple Silicon Mac with 16GB unified memory.
- Reasoning superiority: Phi-4 consistently outperforms other models in its size class for mathematical reasoning and logical problem-solving.
- CPU-friendly efficiency: On CPU-only systems with 16GB+ RAM, Phi-4 generates 5-8 tokens/sec, making it pleasant to use even without a dedicated GPU.
- Instruction following: Microsoft’s training focus on “textbook quality” data results in exceptional instruction following and natural writing capabilities.
That said, the answer ultimately depends on your hardware and use case. If you have a 48GB+ GPU or Mac Studio with 64GB+ unified memory and prioritise coding or multilingual tasks, Qwen 2.5 72B Instruct is unparalleled. If you want the best balance of general intelligence, speed, and agentic/tool-use capabilities on a 12GB GPU, Mistral Nemo 12B is your best choice. But for the widest range of users seeking a practical, pleasant, and intelligent local LLM experience, Phi-4 is the model I would actually run every day.
