Llama Models: The Most Popular Local AI
Meta's Llama is the most widely used open-weight model family in the world. Llama 3.2 and 3.1 models range from 1B to 405B parameters and run on everything from iPhones to high-end workstations. With the largest ecosystem of fine-tunes, tools, and community support, Llama is the safest default choice for local AI.
Meta11 local models
DEVELOPER
Meta
MODELS
11
SIZE RANGE
1B–405B
RAM RANGE
2–320 GB
Key Features
Most popular open-weight model family
Strong general reasoning and instruction following
Huge ecosystem of fine-tunes and tools
Sizes from 1B to 405B parameters
All Llama Models
| Model | Size | Quant | VRAM | Min RAM | Best For | Quality | Ollama |
|---|---|---|---|---|---|---|---|
| Llama 3.2 1B Instruct | 1B | Q4_K_M | 1 GB | 2 GB | Chat | 48 | |
| Llama 3.2 3B Instruct | 3B | Q4_K_M | 2.5 GB | 4 GB | Chat | 66 | |
| Llama 3.1 8B Instruct | 8B | Q4_K_M | 6.5 GB | 12 GB | Chat, Coding | 76 | |
| Llama 3.1 8B Instruct (Q5) | 8B | Q5_K_M | 8 GB | 12 GB | Chat, Coding | 78 | |
| Llama 3.1 70B Instruct | 70B | Q4_K_M | 42 GB | 64 GB | Quality, Coding | 84 | |
| Llama 3.3 70B Instruct | 70B | Q4_K_M | 42 GB | 64 GB | Quality, Coding | 86 | |
| Llama 3.3 70B Instruct (Q8) | 70B | Q8_0 | 75 GB | 96 GB | Quality, Coding | 88 | |
| Llama 3.3 70B Instruct (Q6) | 70B | Q6_K | 57.9 GB | 96 GB | Quality, Coding | 87 | |
| Llama 4 Scout | 109B | Q4_K_M | 67 GB | 96 GB | Long context, Quality, Multimodal | 88 | |
| Llama 4 Maverick | 400B | Q4_K_M | 245 GB | 320 GB | Frontier quality, Long context | 90 | |
| Llama 3.1 405B Instruct | 405B | Q4_K_M | 243 GB | 320 GB | Quality, Reasoning, Coding | 87 |
Device Compatibility
Which Llama models can run on each device class, based on minimum RAM requirements.
| Model | iPhone | Air | Pro | Studio | Mini |
|---|---|---|---|---|---|
| Llama 3.2 1B Instruct (1B) | Excellent | Excellent | Excellent | Excellent | Excellent |
| Llama 3.2 3B Instruct (3B) | Excellent | Excellent | Excellent | Excellent | Excellent |
| Llama 3.1 8B Instruct (8B) | Possible | Possible | Possible | Excellent | Possible |
| Llama 3.1 8B Instruct (Q5) (8B) | Possible | Possible | Possible | Excellent | Possible |
| Llama 3.1 70B Instruct (70B) | No | No | Possible | Possible | Possible |
| Llama 3.3 70B Instruct (70B) | No | No | Possible | Possible | Possible |
| Llama 3.3 70B Instruct (Q8) (70B) | No | No | Possible | Possible | No |
| Llama 3.3 70B Instruct (Q6) (70B) | No | No | Possible | Possible | No |
| Llama 4 Scout (109B) | No | No | Possible | Possible | No |
| Llama 4 Maverick (400B) | No | No | No | Possible | No |
| Llama 3.1 405B Instruct (405B) | No | No | No | Possible | No |
RAM Requirements
1 GB · min 2 GB
2.5 GB · min 4 GB
6.5 GB · min 12 GB
8 GB · min 12 GB
42 GB · min 64 GB
42 GB · min 64 GB
75 GB · min 96 GB
57.9 GB · min 96 GB
67 GB · min 96 GB
245 GB · min 320 GB
243 GB · min 320 GB
Frequently Asked Questions
What is the best Llama model for a MacBook?
Llama 3.2 3B for MacBook Air (8GB RAM) or Llama 3.1 8B for MacBook Pro (16GB+ RAM). The 8B model is the community favorite for general-purpose local AI.
Can Llama 70B run on a Mac?
Yes, but you need at least 48GB RAM (Mac Studio or maxed-out MacBook Pro). The Q4 quantized version uses about 42GB. Expect around 8-12 tokens per second on M4 Max.
What is the difference between Llama 3.1 and 3.2?
Llama 3.2 added small sizes (1B, 3B) optimized for edge devices and mobile. Llama 3.1 covers 8B, 70B, and 405B. For most users, pick 3.2 3B for small devices or 3.1 8B for laptops.
How does Llama compare to Qwen?
Llama has stronger general reasoning and a larger community. Qwen has more size options and better multilingual support. At 7-8B, they are close in quality. Pick based on your use case.